Journal articles: 'Projected image'

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Choi, Eunbin, Younghyeon Park, and Byeungwoo Jeon. "An Implementation of Drone-Projector: Stabilization of Projected Image." Electronic Imaging 2020, no. 3 (January 26, 2020): 332–1. http://dx.doi.org/10.2352/issn.2470-1173.2020.3.mobmu-331.

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A drone-projector equipped with a beam projector mounted on a drone has been investigated in order to develop a projector which can overcome restriction of place on which an image is projected. For the stability, the drone-projector requires its mass to be centered, and the additional weights related to projector should be within the payload of the drone. In addition to this requirement, the drone-projector should be designed to minimize the distortion of image caused by 3D translations or rotations of a drone during its hovering due to vibration of propellers, or global positioning system (GPS) errors. In this paper, we consider rotation of a droneprojector which makes the projected image tilted, keystoned, and shifted. To overcome this problem, we propose a software-based stabilization method which pre-corrects the image to be projected based on flight information. Our experimental results show that the distortion of the projected image due to rotations of the proposed drone-projector is attenuated by applying our stabilization method.

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Shapiro, Alan. "Images: Real and Virtual, Projected and Perceived, from Kepler to Dechales." Early Science and Medicine 13, no. 3 (2008): 270–312. http://dx.doi.org/10.1163/157338208x285044.

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AbstractIn developing a new theory of vision in Ad Vitellionem paralipomena (1604) Kepler introduced a new optical concept, pictura, which is an image projected on to a screen by a camera obscura. He distinguished this pictura from an imago, the traditional image of medieval optics that existed only in the imagination. By the 1670s a new theory of optical imagery had been developed, and Kepler's pictura and imago became real and virtual images, two aspects of a unified concept of image. The new concept of image developed out of a synthesis of Kepler's determination of the geometrical location of a pictura as the limit, or focus, of refracted pencils of rays and the triangulation used by a single eye to determine the perceived location of an imago. The distinction between real and imaginary images was largely developed by Gilles Personne de Roberval and the Jesuits Francesco Eschinardi and Claude François Milliet Dechales.

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Ferrer-Rosell, Berta, and Estela Marine-Roig. "Projected Versus Perceived Destination Image." Tourism Analysis 25, no. 2 (July 8, 2020): 227–37. http://dx.doi.org/10.3727/108354220x15758301241747.

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Due to the spectacular growth of traveler-generated content (TGC), researchers are using TGC as a source of data to analyze the image of destinations as perceived by tourists. In order to analyze a destination's projected image, researchers typically look to websites from destination marketing or management organizations (DMOs). The objective of this study is to calculate the gap between the projected and perceived images of Barcelona, Catalonia, in 2017, using Gartner's classification and applying compositional analysis. The official online press dossier is used as an induced source, the Lonely Planet guidebook as an autonomous source, and a collection of more than 70,000 online travel reviews hosted on TripAdvisor as an organic source. In addition to quantitative content analysis, this study undertakes two thematic analyses: the masterworks of architect Gaudi recognized as UNESCO WHS as part of the cognitive image component and feeling-related keywords as part of the affective image component. The results reveal strong differences between the induced and organic sources, but much smaller differences between the autonomous and organic sources. These results can be useful for DMOs to optimize promotion and supply.

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Zhang, Hua, Yi Kai Shi, Kui Dong Huang, and Qing Chao Yu. "Image Restoration Method Based on Pre-Filtering for Cone-Beam Computed Tomography." Applied Mechanics and Materials 229-231 (November 2012): 1858–61. http://dx.doi.org/10.4028/www.scientific.net/amm.229-231.1858.

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For the problem of image quality degradation of cone-beam Computed Tomography (CBCT) based on flat panel detector (FPD), a constrained least squares iteration (CLSI) restoration method based on pre-filtering is proposed. Firstly, the original projected images are denoised with bilateral filtering algorithm. Then, the denoised projected images are restored with CLSI. Finally, the final restored images are obtained by adding the noise images, which got by subtracting the projected images before and after denoising, to the restored images. The experimental results show that the method well inhibits the noise amplification phenomenon in image restoration, and increases the edge sharpness and contrast-to-noise ratio (CNR) of the projected images and slice images. The CBCT image quality is significantly improved with this method.

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Yakno, Marlina, Junita Mohamad-Saleh, Mohd Zamri Ibrahim, and W. N. A. W. Samsudin. "Camera-projector calibration for near infrared imaging system." Bulletin of Electrical Engineering and Informatics 9, no. 1 (February 1, 2020): 160–70. http://dx.doi.org/10.11591/eei.v9i1.1697.

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Advanced biomedical engineering technologies are continuously changing the medical practices to improve medical care for patients. Needle insertion navigation during intravenous catheterization process via Near infrared (NIR) and camera-projector is one solution. However, the central point of the problem is the image captured by camera misaligns with the image projected back on the object of interest. This causes the projected image not to be overlaid perfectly in the real-world. In this paper, a camera-projector calibration method is presented. Polynomial algorithm was used to remove the barrel distortion in captured images. Scaling and translation transformations are used to correct the geometric distortions introduced in the image acquisition process. Discrepancies in the captured and projected images are assessed. The accuracy of the image and the projected image is 90.643%. This indicates the feasibility of the captured approach to eliminate discrepancies in the projection and navigation images.

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Ourmazd, A., P. Schwander, C. Kisielowski, F. H. Baumann, and Y. Kim. "Measuring projected potential, thickness, and composition from lattice images." Proceedings, annual meeting, Electron Microscopy Society of America 52 (1994): 732–33. http://dx.doi.org/10.1017/s0424820100171390.

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Lattice images obtained by Transmission Electron Microscopy (TEM) are routinely used to infer the subsurface microstructure of crystalline materials. In principle, a lattice image is a map of the sample (Coulomb) potential, projected along a zone axis (see, e.g., [1]). In practice, it is difficult to extract quantitative information from lattice images. This stems from two primary reasons. First, electrons are multiply scattered during their passage through crystalline samples of realistic thickness (>10Å). This results in a complex, highly nonlinear relationship between the sample potential and the characteristics of the lattice image. This relationship changes rapidly with the sample thickness, and thus from point to point over the sample. Second, electromagnetic lenses have severe aberrations. The image details thus depend sensitively on the (contrast) transfer function of the microscope, and hence the lens defocus. It is not possible to establish a general relationship between the sample potential and the image features.

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R. Nisha Dayana, T., and Dr A. Lenin Fred. "An efficient method for image mining using GLCM and neural network." International Journal of Engineering & Technology 7, no. 3.3 (June 8, 2018): 76. http://dx.doi.org/10.14419/ijet.v7i2.33.13859.

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Currently, content-based Image recovery (CBIR) drives for producing approaches which supports viable searching and scanning of vast picture progressive libraries by considering unwavering image texture features and has been a rapidly growing inspection bearing among image information recovery, computer vision, and database. The learning procedure of CBIR is achieved with the Neural Network method together with GLCM feature abstraction in our projected technique. Furthermore, with the ABC algorithm the normal/abnormal arrangement of the medical dataset images is managed. Lastly, to regulate the function of the projected method the solutions were replicated and associated with the available method. In the working platform of MATLAB, the projected method is applied.

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Huang, Kui Dong, Liang Zhang, Kun Bu, and Hua Zhang. "Projected Image Restoration Method Based on Genetic Algorithm for Cone-Beam CT." Applied Mechanics and Materials 401-403 (September 2013): 1406–9. http://dx.doi.org/10.4028/www.scientific.net/amm.401-403.1406.

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For the problem of image quality degradation in cone-beam CT (CBCT) based on flat panel detector (FPD), a genetic algorithm based on pre-segmentation (PS-GA) is proposed for CBCT projected image restoration. According to the characteristic of that most of the area of the projected image is empty and without the tested object, a robust segmentation algorithm is used in this method to segment the smallest rectangle that contains the tested object, and the calculating range is limited to the smallest rectangle by the specially designed genetic algorithm, which significantly reduced the amount of calculated data. The experimental results show that the method raised the edge sharpness, contrast-to-noise ratio (CNR) and average gradient (AG) of the projected images and slice images, and there is no visible artifacts introduced.

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Sugisaka, Jun-ichiro, and Ko Onishi. "Optimal design of photon-sieve holograms for fine-line image generation." Journal of Optics 24, no. 3 (February 4, 2022): 035605. http://dx.doi.org/10.1088/2040-8986/ac4c87.

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Abstract A photon-sieve hologram (PSH) is a computer-generated hologram that can generate fine-line images. As a high-resolution image can be projected directly without using a reducing optical system, it can also be used for short-wavelength radiation, such as x-rays. We propose an optimum design method for the PSH so that a high-quality line image can be projected. We optimised straight-line and L-shaped bent-line images using numerical simulation based on vector diffraction theory and conjugate-gradient methods. This optimisation helped homogenise the intensity of the image and remove unwanted side lobes and spots around the image. We also experimentally examined the bent-line image before and after the optimisation to confirm its effect.

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Picazo, Patricia, Sergio Moreno-Gil, and Dogan Gursoy. "Analysis of the projected image of tourism accommodations: a methodological proposal." International Journal of Contemporary Hospitality Management 31, no. 8 (August 12, 2019): 3325–51. http://dx.doi.org/10.1108/ijchm-05-2017-0276.

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Purpose Examination of the image projected through photographs used in marketing materials can enable managers to identify opportunities for creating differentiated positioning in the marketplace. However, the impact of image projected through photographs has not received much attention in academic literature. This paper aims to establish a methodology using dynamic indices that allow a systematic comparative evaluation of the image projected through photographs used in marketing materials of lodging properties located in competing destinations. It also provides an empirical examination of the type of image projected through photographs of lodging properties in those destinations. Design/methodology/approach Analysis was conducted using a content analysis methodology. A total of 17,187 photographs of 5,820 lodging properties located in 15 different tourism destinations over a period of eight years were examined. Findings Results revealed that the proposed methodology based on dynamic comparative indices is appropriate for determining the projected image of lodging properties. The dynamic indices, which categorise photographs in three main categories: subject (people), activities (actions carried out) and contextualisation (location), allowed a systematic evaluation of the image projected of lodging properties in competing destinations. Results of the empirical analysis indicated important differences in the image projected through photographs among lodging properties located in 15 destinations. Practical implications This study provides the industry and destination marketing organisations (DMOs) with a useful and simple tool for comparatively evaluating the image projected by tourism accommodations. The methodology proposed enables managers to identify the current image and the changes in the image of their lodging properties, their destinations and those of their main competitors over the years, thus providing opportunities for development of more effective differentiation and positioning strategies in their respective target markets. Originality/value The proposed tool provides a methodology that can be used to categorise and evaluate the image represented on the photographs used in marketing materials to ensure the projection of the intended image. Furthermore, the proposed methodological tool enables managers to monitor the image projected through photographs used in competitors’ marketing materials and identify changes in their image projected over time.

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BİCAL, Adil, and Mesude Canan OZTURK. "Projected Image of Turkey in Travel Blogs." Journal of Tourism, Leisure and Hospitality 3, no. 1 (January 31, 2021): 5–17. http://dx.doi.org/10.48119/toleho.823838.

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Jung, Myun Sook, and Young Sil Kang. "The Image of Nursing projected in Newspapers." Journal of Nurses Academic Society 23, no. 1 (1993): 16. http://dx.doi.org/10.4040/jnas.1993.23.1.16.

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Shih, I.-Fu, David B. Chang, Peter L. Garrett, and Norton L. Moise. "Contorted mirror reduction of projected image distortion." Applied Optics 24, no. 8 (April 15, 1985): 1113. http://dx.doi.org/10.1364/ao.24.001113.

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Osa, Atsushi, Kazumi Nagata, Yousuke Honda, Makoto Ichikawa, Ken Matsuda, and Hidetoshi Miike. "Angle Illusion in a Straight Road." Perception 40, no. 11 (January 1, 2011): 1350–56. http://dx.doi.org/10.1068/p7068.

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We report a new angle illusion observed when viewing a real scene involving a straight road. The scene portrays two white lines which outline a traffic lane on a road and converge to a vanishing point. In experiment 1, observers estimated the angle created by these converging lines in this scene or in its image projected onto a screen. Results showed strong underestimation of the angle, ie over 50% for observations of both the real scene and its projected image. Experiment 2 assessed how depth cues in projected images influence the angle illusion. Results showed that this angle illusion disappeared when scene information surrounding convergent lines was removed. In addition, the illusion was attenuated with projection of an inverted scene image. These findings are interpreted in terms of a misadoption of depth information in the processing of angle perception in a flat image; in turn, this induces a massive angle illusion.

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Kemmoku, Yusuke, and Takashi Komuro. "A Large Effective Touchscreen Using a Head-Mounted Projector." Information 9, no. 9 (September 18, 2018): 235. http://dx.doi.org/10.3390/info9090235.

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In our previous work, we proposed a user interface in which a user wears a projector and a depth camera on his or her head and performs touch operations on an image projected on a flat surface. By using the head-mounted projector, images are always projected in front of the user in the direction of the user’s gaze. The image to be projected is changed according to the user’s head pose so as to fix the superimposed image on the surface, which realizes a large effective screen size. In this paper, we conducted an experiment for evaluating the accuracy of registration by measuring the positional and rotational errors between the real world and the superimposed image using our experimental system. As a result, the mean absolute errors of translation were about 10 mm when the user stopped his head, and the delay was estimated to be about 0.2 s. We also discuss the limitations of our prototype and show the direction of future development.

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Lash, Steven J., and James A. Polyson. "Reassessment of Gender Perception in Projected Animal Content." Perceptual and Motor Skills 67, no. 2 (October 1988): 547–53. http://dx.doi.org/10.2466/pms.1988.67.2.547.

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The present study is an extension and refinement of previous research on the gender-relevance of commonly projected animal content. Results again support the projection of gender in animal images, and this tendency is not affected by clarity of image, sex of subject, or subject's sex-type. However, it appears that previous research may have overestimated the number of animals that elicit this phenomenon.

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Li, Jun-Hua, Han-Le Zhang, Qing-Lin Ji, and Wu-Xiang Zhao. "Distortion-Corrected Integral Imaging 3D Display System Based on Lens Array Holographic Optical Element." Symmetry 14, no. 7 (July 20, 2022): 1481. http://dx.doi.org/10.3390/sym14071481.

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We propose a distortion-corrected integral imaging (II) 3D display system based on lens array holographic optical element (LAHOE). The LAHOE is used as a projection screen. The projection beam of the LAHOE is parallel light. Hence, the projection system consists of a spatial light modulator, a reverse projection lens, a relay optical element, and a telecentric lens. The acquired 3D data and the reconstructed 3D image of II are symmetrically related to each other. Therefore, there is lens distortion in the projection system. To avoid affecting the viewing experience of the viewers, the elemental image array (EIA) is projected obliquely on the LAHOE, causing the lateral distortion of the EIA. There is a position deviation in the projection system, so the projected EIA has geometric deformation. Due to the distortion of the EIA, it is difficult to precisely align the projected EIA and LAHOE, which results in serious flip of the reconstructed 3D images. The distortion of the EIA affects the asymmetry of the 3D image reconstruction. Lens distortion can be solved by the distortion compensation method. Lateral and the geometric deformation can be solved by the perspective transformations in computer graphics. After correction, the undistorted EIA is projected, and the projected EIA on the LAHOE has little distortion. In the process of 3D image reconstruction, the causes of asymmetry affecting 3D image reconstruction are analyzed, and the issues that generate these asymmetric factors are addressed. Experimental results indicate that a better 3D display effect is achieved.

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ITO, YASUAKI, and KOJI NAKANO. "FM SCREENING BY THE LOCAL EXHAUSTIVE SEARCH, WITH HARDWARE ACCELERATION." International Journal of Foundations of Computer Science 16, no. 01 (February 2005): 89–104. http://dx.doi.org/10.1142/s0129054105002887.

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The main contribution of this paper is to show a new approach for FM screening which we call Local Exhaustive Search (LES) method, and to present ways to accelerate the computation using an FPGA. FM screening, as opposed to conventional AM screening, keeps unit dot size when converting an original gray-scale image into the binary image for printing. FM screening pays great attention to generate moiré-free binary images reproducing continuous-tone and fine details of original photographic images. Our basic approach for FM screening is to generate a binary image whose projected image onto human eyes is very close to the original image. The projected image is computed by applying a Gaussian filter to the binary image. LES performs an exhaustive search for each of the small square subimages in the binary image and replaces the subimage by the best binary pattern. The exhaustive search is repeated until no more improvement is possible. The experimental results show that LES produces a high quality and sharp binary image. We also implemented LES on an FPGA to accelerate the computation and achieved a speedup factor of up to 51 over the software implementations.

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Ashwini P, Sherin Antony, and Kanchana V. "Categorizing the stages of lung cancer using Multi SVM Classifier." International Journal of Research in Pharmaceutical Sciences 10, no. 3 (July 25, 2012): 2323–28. http://dx.doi.org/10.26452/ijrps.v10i3.1472.

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Detection of cancer is the utmost fascinating analysis space for scientists in the early period. The projected method is meant to identify cancer in the beginning phase. The projected method comprises several phases, such as image acquisition, pre-processing, segmentation, feature extraction, and classification. In our proposed work, segmentation is done to fragment the CT image. We use solid feature extraction (GLCM) technique to extract certain essential features from the segmented images. Further extracted features are considered for classification (Multi SVM) process to check whether cancerous or non-cancerous.

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Duan, Xialei, Lawal Mohammed Marafa, Chung-Shing Chan, Han Xu, and Lewis T. O. Cheung. "Measuring the Gaps in the Projected Image and Perceived Image of Rural Tourism Destinations in China’s Yangtze River Delta." Sustainability 12, no. 12 (June 23, 2020): 5121. http://dx.doi.org/10.3390/su12125121.

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Destination Marketing Organizations (DMOs) at all levels have an ultimate goal of building strong and positive images for their destinations. However, the projected image from the supply side is not necessarily the mirror of the perceived image from the demand side. This study adopted the content analysis method to evaluate the projected image and perceived image of rural destinations in China to see whether there is any discrepancy between and within the two categories. Comparative analysis of different information sources including web contents and on-site visitor interviews were processed. The evaluation of image congruency demonstrates that official websites focus more on cognitive image elements (knowledge and beliefs of the place). Besides promoting attractions, it provides information on geography background and promotes local culture. Business web content promotes attractions, package tour, and activities which can generate revenue. The perceived image includes more sentiment contents: on-site visitors expressed more negative attitude, but social media comments are relatively positive.

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Huang, Jin, Feiping Nie, Heng Huang, and Chris Ding. "Supervised and Projected Sparse Coding for Image Classification." Proceedings of the AAAI Conference on Artificial Intelligence 27, no. 1 (June 30, 2013): 438–44. http://dx.doi.org/10.1609/aaai.v27i1.8691.

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Classic sparse representation for classification (SRC) method fails to incorporate the label information of training images, and meanwhile has a poor scalability due to the expensive computation for l_1 norm. In this paper, we propose a novel subspace sparse coding method with utilizing label information to effectively classify the images in the subspace. Our new approach unifies the tasks of dimension reduction and supervised sparse vector learning, by simultaneously preserving the data sparse structure and meanwhile seeking the optimal projection direction in the training stage, therefore accelerates the classification process in the test stage. Our method achieves both flat and structured sparsity for the vector representations, therefore making our framework more discriminative during the subspace learning and subsequent classification. The empirical results on 4 benchmark data sets demonstrate the effectiveness of our method.

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Butler, A. "Screen/Space: the Projected Image in Contemporary Art." Screen 52, no. 4 (December 1, 2011): 531–35. http://dx.doi.org/10.1093/screen/hjr047.

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Cassar, Ignaz. "Viewed from Behind: The Projected Image and itsDoppelgänger." Parallax 14, no. 2 (April 2008): 115–25. http://dx.doi.org/10.1080/13534640801990616.

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Draper, Norman R., and Dennis K. J. Lin. "Characterizing projected designs: repeat and mirror-image runs." Communications in Statistics - Theory and Methods 24, no. 3 (January 1995): 775–95. http://dx.doi.org/10.1080/03610929508831521.

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Chen, X., and X. B. Huang. "Evaluating Fabric Pilling with Light-Projected Image Analysis." Textile Research Journal 74, no. 11 (November 2004): 977–81. http://dx.doi.org/10.1177/004051750407401107.

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BEECH, John R., and James WHITTAKER. "WHAT IS THE FEMALE IMAGE PROJECTED BY SMOKING?" PSYCHOLOGIA -An International Journal of Psychology in the Orient 44, no. 3 (2001): 230–36. http://dx.doi.org/10.2117/psysoc.2001.230.

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FURUYA, Nobuyuki, Tsuyoshi SHIMIZU, Akihito ITO, and Masaru ITO. "Stereo Image Measuring Method Based on Projected Invariant." Journal of the Japan Society for Precision Engineering 78, no. 10 (2012): 875–79. http://dx.doi.org/10.2493/jjspe.78.875.

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Hunter, William Cannon. "Projected Destination Image: A Visual Analysis of Seoul." Tourism Geographies 14, no. 3 (August 2012): 419–43. http://dx.doi.org/10.1080/14616688.2011.613407.

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Maalek, Reza, and Derek D. Lichti. "Correcting the Eccentricity Error of Projected Spherical Objects in Perspective Cameras." Remote Sensing 13, no. 16 (August 18, 2021): 3269. http://dx.doi.org/10.3390/rs13163269.

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Projective transformation of spheres onto images produce ellipses, whose centers do not coincide with the projected center of the sphere. This results in an eccentricity error, which must be treated in high precision metrology. This article provides closed formulations for modeling this error in images to enable 3-dimensional (3D) reconstruction of the center of spherical objects. The article also provides a new direct robust method for detecting spherical pattern in point clouds. It was shown that the eccentricity error in an image has only one component in the direction of the major axis of the ellipse. It was also revealed that the eccentricity is zero if and only if the center of the projected sphere lies on the camera’s perspective center. The effectiveness of the robust sphere detection and the eccentricity error modeling method was evaluated on simulated point clouds of spheres and real-world images, respectively. It was observed that the proposed robust sphere fitting method outperformed the popular M-estimator sample consensus in terms of radius and center estimation accuracy by a factor of 13, and 14 on average, respectively. Using the proposed eccentricity adjustment, the estimated 3D center of the sphere using modeled eccentricity was superior to the unmodeled case. It was also observed that the accuracy of the estimated 3D center using modeled eccentricity continuously improved as the number of images increased, whereas the unmodeled eccentricity did not show improvements after eight image views. The results of the investigation show that: (i) the proposed method effectively modeled the eccentricity error, and (ii) the effects of eliminating the eccentricity error in the 3D reconstruction become even more pronounced in a larger number of image views.

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Dong, Chun Bo, Xing Jun Hu, Yan Wang, and Li Min Fu. "Realization of Car’s Frontal Projected Area Based on OpenCV." Applied Mechanics and Materials 300-301 (February 2013): 1673–76. http://dx.doi.org/10.4028/www.scientific.net/amm.300-301.1673.

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Digital image processing technology applied to the field of automotive body development, especially the aerodynamic development of the external shape of automobile. This method and its corresponding software improve the efficiency compared with other traditional fluid software tools in processing the car’s front area, reduce artificial error, and have high accuracy. Digital image processing algorithms used in this article includes Image Gray, Median Filtering, Image Segmentation, Contour Extraction and so on.

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Wang, Jiali, and Yannan Chen. "Digital Surface Model Refinement Based on Projected Images." Photogrammetric Engineering & Remote Sensing 87, no. 3 (March 1, 2021): 181–87. http://dx.doi.org/10.14358/pers.87.3.181.

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Currently, the practical solution to remove the errors and artifacts in the digital surface models (DSM ) through stereo images is still manual or semiautomatic editing those affected patches. Although some degrees of semiautomation can be gained, the DSM refinement remains a labor consuming and expensive process. This paper proposes a new method to correct errors in DSM or/and refine an existing coarse DSM. The method employs the concept of projected images together with some image matching techniques to correct/ refine the affected regions in DSM. Since projected images are used, the proposed method can greatly simplify the complicated coordinate transformations and pixel resampling; therefore, the errors/artifacts in DSM can be amended more efficiently and accurately. Several experiments demonstrate the practical usefulness of the proposed method under some scenarios, and some potential improvements are also pointed out to accommodate the various needs during refining DSM.

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Vizilter, Yu V., O. V. Vygolov, and S. Yu Zheltov. "Morphological analysis of mosaic shapes with directed relationships based on attribute and relational model representations." Computer Optics 5, no. 45 (September 2021): 756–66. http://dx.doi.org/10.18287/2412-6179-co-843.

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We introduce attribute and relational representations of mosaic image models with directed relationships between regions. Attribute representations of asymmetric relational models based on stacking, ranking and integral descriptions are considered. We propose some morphological shape similarity measures based on relational models. We show that using the same oriented relational model, various morphological operators can be constructed, in particular, of Serra- or Pyt’ev type. Some constructive methods for the design of such morphological operators in an attribute and relational domains are proposed. From this consideration we also extract a new morophlogical scheme for two-stage mutual adaptive image-and-shape joint filtering: at the first step, the shape is simplified (projected) with regard to the image to be projected, and at the second step, the image is simplified (projected) with regard to the simplified (projected) shape.

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Vizilter, Yu V., O. V. Vygolov, and S. Yu Zheltov. "Morphological analysis of mosaic shapes with directed relationships based on attribute and relational model representations." Computer Optics 5, no. 45 (September 2021): 756–66. http://dx.doi.org/10.18287/2412-6179-co-843.

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We introduce attribute and relational representations of mosaic image models with directed relationships between regions. Attribute representations of asymmetric relational models based on stacking, ranking and integral descriptions are considered. We propose some morphological shape similarity measures based on relational models. We show that using the same oriented relational model, various morphological operators can be constructed, in particular, of Serra- or Pyt’ev type. Some constructive methods for the design of such morphological operators in an attribute and relational domains are proposed. From this consideration we also extract a new morophlogical scheme for two-stage mutual adaptive image-and-shape joint filtering: at the first step, the shape is simplified (projected) with regard to the image to be projected, and at the second step, the image is simplified (projected) with regard to the simplified (projected) shape.

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Yang, Tao, Yue Liu, and You Lu. "A Rapid Auto-Caliberation Method in Projector-Camera System." Applied Mechanics and Materials 58-60 (June 2011): 2308–13. http://dx.doi.org/10.4028/www.scientific.net/amm.58-60.2308.

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A precise, fast, and fully automatic calibration method is proposed to address the shortcomings in currently used large-scale interactive camera-projector systems. These shortcomings include a small number of calibration points used in manual calibration, large errors, huge time consumption, and lack of professional quality operations. The proposed method applies mechanical wavelength switching in the projected image to capture multi-regional vertices. The co-linearity of each point in the projected images is calculated to determine the actual location of the interactive points in the projected image. The point-by-point computation adopted in the method promotes the automatic elimination of uncorrectable systematic errors in large-scale optical devices. The automatic error elimination not only increases the accuracy of the interactive system and reduces the complexity of system installation, but also increases the flexibility of the interactive system.

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Nguyen, T. N., J. M. Huntley, R. Burguete, and C. R. Coggrave. "Combining digital image correlation and projected fringe techniques on a multi-camera multi-projector platform." Journal of Physics: Conference Series 181 (August 1, 2009): 012076. http://dx.doi.org/10.1088/1742-6596/181/1/012076.

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Mittal, Abhishek. "Hybrid Classification for Face Spoof Detection." International Journal for Research in Applied Science and Engineering Technology 9, no. 11 (November 30, 2021): 1732–39. http://dx.doi.org/10.22214/ijraset.2021.39085.

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Abstract: ML (machine learning) is consisted of a method of recognizing face. This technique is useful for the attendance system. Two sets are generated for testing and training phases in order to segment the image, to extract the features and develop a dataset. An image is considered as a testing set; the training set is contrasted when it is essential to identify an image. An ensemble classifier is implemented to classify the test images as recognized or non-recognized. The ensemble algorithm fails to acquire higher accuracy as it classifies the data in two classes. Thus, GLCM (Grey Level Co-occurrence Matrix) is projected for analyzing the texture features in order to detect the face. The attendance of the query image is marked after detecting the face. The simulation outcomes revealed the superiority of the projected technique over the traditional methods concerning accuracy. Keywords: DWT, GLCM, KNN, Decision Tree

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Deng, Shuwen, Yuanjin Li, and Dianhua Wang. "Streak Metal Artifact Reduction Based on Sinogram Fusion and Tissue-Class Model in CT Images." Wireless Communications and Mobile Computing 2022 (April 30, 2022): 1–7. http://dx.doi.org/10.1155/2022/8021862.

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The presence of streak metal artifacts seriously degrades the diagnostic value and deteriorates the qualities of CT images. Analyzing the causes and classical streak metal artifact reduction (MAR) methods, the paper proposes the streak metal artifact reduction method based on sinogram fusion and tissue-class mode for CT images (F-MAR). Firstly, the original CT images are corrected using a linear interpolation streak metal artifact reduction (L-MAR) scheme in the raw data domain. Subsequently, to preserve the edge information, the metal artifact-reduced images are then smoothed into smoothed images (tissue-class model) by using the mean filter. Segment the original CT image that contained the streak artifacts. The original CT image and the CT image that contained high-density material are projected into the original sinogram and the high density material sinogram, respectively. Secondly, the simple linear interpolation is used to correct the CT original CT image into the corrected CT image. The mean filter is applied in the corrected CT image. The corrected CT image is projected into the corrected sinogram. Thirdly, according to the position of the high density material sinogram located in the original sinogram and the corrected sinogram, the original position sinogram included in the original sinogram and the corrected position sinogram included in the corrected sinogram are, respectively, obtained. The two sinograms are fused into the fused sinogram. The fused sinogram, the original sinogram, and the high-density material sinogram are fused into the final sinogram. Finally, the filtered back projection reconstruction algorithm is used to reconstruct the final sinogram into the reconstructed CT image. The reconstructed CT image and high density material image are fused into the final image. The experimentation results show that the method proposed in the paper can obtain better correction effect than the classical correction methods in vision.

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Victorino, Gonçalo Filipe, Ricardo Braga, José Santos-Victor, and Carlos M. Lopes. "Yield components detection and image-based indicators for non-invasive grapevine yield prediction at different phenological phases." OENO One 54, no. 4 (October 29, 2020): 833–48. http://dx.doi.org/10.20870/oeno-one.2020.54.4.3616.

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Forecasting vineyard yield with accuracy is one of the most important trends of research in viticulture today. Conventional methods for yield forecasting are manual, require a lot of labour and resources and are often destructive. Recently, image-analysis approaches have been explored to address this issue. Many of these approaches encompass cameras deployed on ground platforms that collect images in proximal range, on-the-go. As the platform moves, yield components and other image-based indicators are detected and counted to perform yield estimations. However, in most situations, when image acquisition is done in non-disturbed canopies, a high fraction of yield components is occluded. The present work’s goal is twofold. Firstly, to evaluate yield components’ visibility in natural conditions throughout the grapevine’s phenological stages. Secondly, to explore single bunch images taken in lab conditions to obtain the best visible bunch attributes to use as yield indicators.In three vineyard plots of red (Syrah) and white varieties (Arinto and Encruzado), several canopy 1 m segments were imaged using the robotic platform Vinbot. Images were collected from winter bud stage until harvest and yield components were counted in the images as well as in the field. At pea-sized berries, veraison and full maturation stages, a bunch sample was collected and brought to lab conditions for detailed assessments at a bunch scale.At early stages, all varieties showed good visibility of spurs and shoots, however, the number of shoots was only highly and significantly correlated with the yield for the variety Syrah. Inflorescence and bunch occlusion reached high percentages, above 50 %. In lab conditions, among the several bunch attributes studied, bunch volume and bunch projected area showed the highest correlation coefficients with yield. In field conditions, using non-defoliated vines, the bunch projected area of visible bunches presented high and significant correlation coefficients with yield, regardless of the fruit’s occlusion.Our results show that counting yield components with image analysis in non-defoliated vines may be insufficient for accurate yield estimation. On the other hand, using bunch projected area as a predictor can be the best option to achieve that goal, even with high levels of occlusion.

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Chan, Chung-Shing, and Yunan Zhang. "Matching projected image with perceived image for geotourism development: a qualitative-quantitative integration." Asian Geographer 35, no. 2 (July 3, 2018): 143–60. http://dx.doi.org/10.1080/10225706.2018.1527235.

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Matsuoka, R., and S. Maruyama. "ECCENTRICITY ON AN IMAGE CAUSED BY PROJECTION OF A CIRCLE AND A SPHERE." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences III-5 (June 6, 2016): 19–26. http://dx.doi.org/10.5194/isprsannals-iii-5-19-2016.

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Circular targets on a plane are often utilized in photogrammetry, particularly in close range photogrammetry, while spherical targets are sometimes utilized in industrial applications. Both a circle and a sphere are projected as an ellipse onto an image. There is an eccentricity on an image between the centre of the projected ellipse and the projected location of the centre of a circle or a sphere. Since only the centre of the projected ellipse is measured, the correction of the eccentricity is considered to be necessary for highly accurate measurement. This paper shows a process to derive general formulae to calculate an eccentricity of a circle and a sphere using the size and the location of a circle or a sphere, and the focal length, the position and the attitude of a camera. Furthermore the paper shows methods to estimate the eccentricity of a circle and a sphere from the equation of the projected ellipse of a circle or a sphere on an image.

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Matsuoka, R., and S. Maruyama. "ECCENTRICITY ON AN IMAGE CAUSED BY PROJECTION OF A CIRCLE AND A SPHERE." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences III-5 (June 6, 2016): 19–26. http://dx.doi.org/10.5194/isprs-annals-iii-5-19-2016.

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Circular targets on a plane are often utilized in photogrammetry, particularly in close range photogrammetry, while spherical targets are sometimes utilized in industrial applications. Both a circle and a sphere are projected as an ellipse onto an image. There is an eccentricity on an image between the centre of the projected ellipse and the projected location of the centre of a circle or a sphere. Since only the centre of the projected ellipse is measured, the correction of the eccentricity is considered to be necessary for highly accurate measurement. This paper shows a process to derive general formulae to calculate an eccentricity of a circle and a sphere using the size and the location of a circle or a sphere, and the focal length, the position and the attitude of a camera. Furthermore the paper shows methods to estimate the eccentricity of a circle and a sphere from the equation of the projected ellipse of a circle or a sphere on an image.

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Shimoi, Mototsugu, Naoya Hara, and Ryuji Satoh. "The visibility of projected image by high-lumen OHP." JOURNAL OF THE ILLUMINATING ENGINEERING INSTITUTE OF JAPAN 81, Appendix (1997): 132. http://dx.doi.org/10.2150/jieij1980.81.appendix_132.

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Fukaya, Takashi, Hideo Fujikake, Yuko Yamanouchi, and Hideki Mitsumine. "A Studio Presentation System Using an Intermittently Projected Image." Journal of the Institute of Image Information and Television Engineers 59, no. 2 (2005): 257–64. http://dx.doi.org/10.3169/itej.59.257.

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Li, Xiao, Min Fang, and Ju-Jie Zhang. "Projected Transfer Sparse Coding for cross domain image representation." Journal of Visual Communication and Image Representation 33 (November 2015): 265–72. http://dx.doi.org/10.1016/j.jvcir.2015.09.018.

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Goossens, B., A. Pizurica, and W. Philips. "Image Denoising Using Mixtures of Projected Gaussian Scale Mixtures." IEEE Transactions on Image Processing 18, no. 8 (August 2009): 1689–702. http://dx.doi.org/10.1109/tip.2009.2022006.

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Naveed, Tayyab, Azmat Hussain, and Yueqi Zhong. "Reducing fabric wastage through image projected virtual marker (IPVM)." Textile Research Journal 88, no. 14 (April 19, 2017): 1571–80. http://dx.doi.org/10.1177/0040517517703605.

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In apparel manufacturing, more than 50% of the total cost is consumed by the fabric in comparison to the rest of the materials. The efficient use of fabric may result in the reduction of considerable expenditure and efforts. Therefore, the purpose of this study is to propose an image projected virtual marker (IPVM) onto the surface of fabric layers/plies to improve fabric utilization and visual quality control. 20 garment production orders are scheduled for experimental work to investigate the utilization of fabrics with imperfections. The statistical analysis indicates a 3.5%–4% improvement in the fabric utilization, a 22% improvement in throughput time of visual inspection, and a 25% reduction of labor intensity during visual inspection in the cutting room. The result implies that the proposed method is an efficient approach to improve fabric utilization and cost reduction.

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Nghiêm-Phú, Bình. "Projected Country Image: An Investigation of Provinces/Cities’ Logos." Asia Pacific Journal of Tourism Research 20, sup1 (February 13, 2015): 1466–85. http://dx.doi.org/10.1080/10941665.2014.998690.

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Tanaka, Masaru, Takio Kurita, and Shinji Umeyama. "Image understanding via representation of the projected motion group." Pattern Recognition Letters 15, no. 10 (October 1994): 993–1001. http://dx.doi.org/10.1016/0167-8655(94)90031-0.

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Zhao, Xue Jin, and Cheng Rui Zhang. "A New Camera and Projector Calibration Method Based on Discrete Computation." Applied Mechanics and Materials 229-231 (November 2012): 1171–75. http://dx.doi.org/10.4028/www.scientific.net/amm.229-231.1171.

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This paper presents a novel method for the calibration of camera and projector based on discrete computation, which uses a linear moving chessboard and project plane to get a calibration database for camera and projector. The camera database contains multi-layers data of the captured chessboard corners and their corresponding practical coordinates in the system. Then by using this database and interpolation algorithm, we can calculate the accurate position for each given pixel position in the captured image. After this we change the chessboard with a white scene and project a chessboard image to the plane. By capturing the projected image and computing the practical position for the corners in the image, we can get a relationship between practical coordinates and the projected image pixels. So another database for the project image and the practical coordinates is established. By using these two databases, we can define the light line for the pixels in a camera captured image and projected image, which can be used for 3D scanning system and other industrial systems, like mask-image projection stereo lithography rapid prototyping system.

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Sun, Wei, Shoulian Tang, and Fang Liu. "Examining Perceived and Projected Destination Image: A Social Media Content Analysis." Sustainability 13, no. 6 (March 18, 2021): 3354. http://dx.doi.org/10.3390/su13063354.

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Destination image has been extensively studied in tourism and marketing, but the questions surrounding the discrepancy between the projected (perceptions from the National Tourism Organizations) and perceived destination image (perceptions from tourists) as well as how the discrepancy may influence sustainable experience remain unclear. Poor understanding of the discrepancy may cause tourist confusion and misuse of resources. The aim of this study is to empirically investigate if the perceived (by tourists) and projected (by NTOs) destination image are significantly different in both cognitive and affective aspects. Through a comprehensive social media content analysis of the NTO-generated and tourist-generated-contents (TGC), the current study identifies numerous gaps between the projected and perceived destination image, which offers some important theoretical and practical implications on destination management and marketing.

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Journal articles on the topic 'Projected image'

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