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Journal articles on the topic 'Descriptor transformation'

Author: Grafiati

Published: 30 May 2022

Last updated: 31 July 2025

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1

Xiong, Fengguang, Yu Kong, Xinhe Kuang, et al. "A Multi-Scale Covariance Matrix Descriptor and an Accurate Transformation Estimation for Robust Point Cloud Registration." Applied Sciences 14, no. 20 (2024): 9375. http://dx.doi.org/10.3390/app14209375.

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This paper presents a robust point cloud registration method based on a multi-scale covariance matrix descriptor and an accurate transformation estimation. Compared with state-of-the-art feature descriptors, such as FPH, 3DSC, spin image, etc., our proposed multi-scale covariance matrix descriptor is superior for dealing with registration problems in a higher noise environment since the mean operation in generating the covariance matrix can filter out most of the noise-damaged samples or outliers and also make itself robust to noise. Compared with transformation estimation, such as feature mat

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CHENG, D., S. Q. XIE, and E. HÄMMERLE. "LOCAL DESCRIPTORS BASED ON COLOR IMAGES." International Journal of Information Acquisition 06, no. 04 (2009): 281–301. http://dx.doi.org/10.1142/s0219878909002004.

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This paper investigates local descriptor methods utilizing color images instead of grayscale images to improve the uniqueness of the local descriptors. A color model was utilized in order to be invariant to illumination condition changes. Two local descriptor methods, namely color local descriptor and hybrid local descriptor methods, were developed. Results from the experiments conducted show that these methods are more robust against a variety of image transformation and illumination condition changes compared to existing methods.

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Liu, Cuiyin, Jishang Xu, and Feng Wang. "A Review of Keypoints’ Detection and Feature Description in Image Registration." Scientific Programming 2021 (December 1, 2021): 1–25. http://dx.doi.org/10.1155/2021/8509164.

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For image registration, feature detection and description are critical steps that identify the keypoints and describe them for the subsequent matching to estimate the geometric transformation parameters between two images. Recently, there has been a large increase in the research methods of detection operators and description operators, from traditional methods to deep learning methods. To solve the problem, that is, which operator is suitable for specific application problems under different imaging conditions, the paper systematically reviewed commonly used descriptors and detectors from art

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Mani, M. Radhika, and T. Srikanth. "An Innovative Vortex based Complex Potential Signature for Shape based Object Recognition." International Journal of Computational and Applied Mathematics & Computer Science 2 (June 4, 2022): 39–43. http://dx.doi.org/10.37394/232028.2022.2.8.

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An Innovative approach for representation and description of shape components for object recognition based on complex potential is proposed. In the complex plane, the flow of velocity is a crucial factor to discriminate different shapes. Hence, the present paper computes the potential flow by transforming the shape of the input object into complex plane. The present paper computes the Vortex based Complex Potential signature (VCP) by considering the radial lines as Equipotential lines and the circles as streamlines. The proposed VCP signature is described with the Fourier transformation for th

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Mashtalir, Sergii V., and Dmytro P. Lendel. "Video fragment processing by Ky Fan norm." Applied Aspects of Information Technology 7, no. 1 (2024): 59–68. http://dx.doi.org/10.15276/aait.07.2024.5.

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In this study, we focused on the formalization of video frame descriptions in the context of solving video segmentation problem. Since native video data can have various sizes, dividing each frame into blocks allows present image frame as a square matrix for a formal description. The frame block is a matrix of arbitrary dimensions. The ability to skip the step of matrix transformation to a square dimension or vectorization using some descriptor allows to reduce computational costs, freeing up computational resources required for this transformation. In our study, we used Ky Fan norm value as i

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ELHADY, GAMAL F. "3D STRUCTURE FROM MOTION WITH FOURIER DESCRIPTOR TRANSFORMATION." International Journal of Pattern Recognition and Artificial Intelligence 27, no. 05 (2013): 1355006. http://dx.doi.org/10.1142/s0218001413550069.

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The simultaneous recovery of three-dimensional (3D) structure from motion (SfM) for the sequences of images, is one of the more difficult problems in computer vision. Classical approaches to the problem rely on using algebraic techniques to solve for these unknowns given two or more image. Motion analysis and 3D shape estimation based on the estimated motion is an important problem in computer vision. The correspondence problem is an important tool in SfM where in this paper a general 3D motion based on a simple rotation, tilt, roll and translation is proposed, and then is used for 3D shape es

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Wang, Xu Guang, and Jie Su. "A Novel Descriptor for Line (Curve) Matching." Applied Mechanics and Materials 48-49 (February 2011): 92–97. http://dx.doi.org/10.4028/www.scientific.net/amm.48-49.92.

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This paper defines a new image feature called Harris feature vector, which is able to describe the image gradient distribution in an effective way. By computing the mean and the standard deviation of the Harris feature vector in a local image region, novel descriptors are constructed for line (curve) matching which are invariable to image rigid transformation and linear intensity change. Experimental evidence suggests that the novel descriptor for line (curve) matching performs well.

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Hamdini, Rabah, Nacira Diffellah, and Abderrahmane Namane. "Color Based Object Categorization Using Histograms of Oriented Hue and Saturation." Traitement du Signal 38, no. 5 (2021): 1293–307. http://dx.doi.org/10.18280/ts.380504.

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In the last few years, there has been a lot of interest in making smart components, e.g. robots, able to simulate human capacity of object recognition and categorization. In this paper, we propose a new revolutionary approach for object categorization based on combining the HOG (Histograms of Oriented Gradients) descriptors with our two new descriptors, HOH (Histograms of Oriented Hue) and HOS (Histograms of Oriented Saturation), designed it in the HSL (Hue, Saturation and Luminance) color space and inspired by this famous HOG descriptor. By using the chrominance components, we have succeeded

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D, Hema, and Kannan S. "Patch-SIFT: Enhanced feature descriptor to learn human facial emotions using an Ensemble approach." Indian Journal of Science and Technology 14, no. 21 (2021): 1740–47. https://doi.org/10.17485/IJST/v14i21.2261.

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Abstract <strong>Background:</strong> Having experienced more than a year of pandemic, a variety of applications such as online classrooms, virtual office meetings, conferences, online games, Social media & Networks, Mobile applications, and many other infotainment areas have made humans live with gadgets and respond to them. However, all these applications have an impact on human behavioral transformation. It is very significant for employers to understand the emotions of their employees in the era of online office & work from home concept to increase productivity. Learning and i

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Veinidis, Christos, Antonios Danelakis, Ioannis Pratikakis, and Theoharis Theoharis. "Effective Descriptors for Human Action Retrieval from 3D Mesh Sequences." International Journal of Image and Graphics 19, no. 03 (2019): 1950018. http://dx.doi.org/10.1142/s0219467819500189.

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Two novel methods for fully unsupervised human action retrieval using 3D mesh sequences are presented. The first achieves high accuracy but is suitable for sequences consisting of clean meshes, such as artificial sequences or highly post-processed real sequences, while the second one is robust and suitable for noisy meshes, such as those that often result from unprocessed scanning or 3D surface reconstruction errors. The first method uses a spatio-temporal descriptor based on the trajectories of 6 salient points of the human body (i.e. the centroid, the top of the head and the ends of the two

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Xu, Zheng Guang, Chen Chen, and Xu Hong Liu. "An Efficient View-Point Invariant Detector and Descriptor." Advanced Materials Research 659 (January 2013): 143–48. http://dx.doi.org/10.4028/www.scientific.net/amr.659.143.

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Many computer vision applications need keypoint correspondence between images under different view conditions. Generally speaking, traditional algorithms target applications with either good performance in invariance to affine transformation or speed of computation. Nowadays, the widely usage of computer vision algorithms on handle devices such as mobile phones and embedded devices with low memory and computation capability has proposed a target of making descriptors faster to computer and more compact while remaining robust to affine transformation and noise. To best address the whole process

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Volkov, V. V., and E. A. Shvets. "Neural network algorithm for optical-SAR image registration based on a uniform grid of points." Computer Optics 48, no. 4 (2024): 610–18. http://dx.doi.org/10.18287/2412-6179-co-1426.

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The paper considers the problem of satellite multimodal image registration, in particular, optical and SAR (Synthetic Aperture Radar). Such algorithms are used in object detection, change detection, navigation. The paper considers algorithms for optical-to-SAR image registration in conditions of rough image pre-alignment. It is known that optical and SAR images have an inaccuracy in registration with georeference (up to 100 pixels with a spatial resolution of 10 m/pixel). This paper presents a neural network algorithm for optical-to-SAR image registration based on descriptors calculated for a

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Laukikkumar, K. Patel, and I. Patel Manish. "Feature Based Image Registration Using ORB and CNN for Remote Sensing Images." Indian Journal of Science and Technology 16, no. 42 (2023): 3803–13. https://doi.org/10.17485/IJST/v16i42.1782.

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Abstract <strong>Objectives:</strong> To improve image registration by reducing the estimation error of the rotation transformation parameter under illumination change effect in remote sensing images using Oriented Fast and Rotated Brief (ORB) and Convolutional Neural Network (CNN). Also, to reduce computational complexity that can be increased due to use of CNN. <strong>Methods:</strong> The image registration process aligns two or more images geometrically and a novel feature based approaches for image registration is proposed here, where ORB and CNN are used to estimate rotat

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Martey, Ezekiel Mensah, Hang Lei, Xiaoyu Li, and Obed Appiah. "Image Representation Using Stacked Colour Histogram." Algorithms 14, no. 8 (2021): 228. http://dx.doi.org/10.3390/a14080228.

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Image representation plays a vital role in the realisation of Content-Based Image Retrieval (CBIR) system. The representation is performed because pixel-by-pixel matching for image retrieval is impracticable as a result of the rigid nature of such an approach. In CBIR therefore, colour, shape and texture and other visual features are used to represent images for effective retrieval task. Among these visual features, the colour and texture are pretty remarkable in defining the content of the image. However, combining these features does not necessarily guarantee better retrieval accuracy due to

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Liao, Fucheng, Zhihua Xue, and Jiang Wu. "Design of an Optimal Preview Controller for a Class of Linear Discrete-Time Descriptor Systems." Mathematical Problems in Engineering 2017 (2017): 1–9. http://dx.doi.org/10.1155/2017/1414029.

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The preview control problem of a class of linear discrete-time descriptor systems is studied. Firstly, the descriptor system is decomposed into a normal system and an algebraic equation by the method of the constrained equivalent transformation. Secondly, by applying the first-order forward difference operator to the state equation, combined with the error equation, the error system is obtained. The tracking problem is transformed into the optimal preview control problem of the error system. Finally, the optimal controller of the error system is obtained by using the related results and the op

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Tian, Ying, and De Bin Zhang. "Ear Recognition Based on Point Feature." Applied Mechanics and Materials 380-384 (August 2013): 3840–45. http://dx.doi.org/10.4028/www.scientific.net/amm.380-384.3840.

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In order to improve recognition rate of human ear, a method based on point feature of image for ear recognition is proposed in this paper. Firstly force field transformation theory is applied to human ear image two times in our method. It can extract the structural feature points and contour feature points of ear respectively and compose feature point set. Then feature points described by the scale invariant feature transformation descriptor. At last nearest neighbor classifier is employed for ear recognition. Feature points extracted from ear image using force field transformation are stable,

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Yan, Shen Hai, Xian Tong Huang, and Yang Liu. "A Novel Texture Spectrum Descriptor." Applied Mechanics and Materials 397-400 (September 2013): 1494–99. http://dx.doi.org/10.4028/www.scientific.net/amm.397-400.1494.

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A concept of equivalence classes of texture pattern is put forward according to the visual consistency between the rotation texture and the flip texture. An improved texture spectrum descriptor (iTS) is proposed based on the equivalence classes. The iTS depicts the grayscale variation pattern of the pixels in the image neighbour domain and denotes the texture content of an image with a histogram of texture spectrum. Compared with the basic texture spectrum descriptor (TS), local binary pattern (LBP) and Shis local binary pattern (sLBP), iTS has best precision in the image retrieval experiments

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Lin, Zhiyang, Jihua Zhu, Zutao Jiang, Yujie Li, Yaochen Li, and Zhongyu Li. "Merging Grid Maps in Diverse Resolutions by the Context-based Descriptor." ACM Transactions on Internet Technology 21, no. 4 (2021): 1–21. http://dx.doi.org/10.1145/3403948.

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Building an accurate map is essential for autonomous robot navigation in the environment without GPS. Compared with single-robot, the multiple-robot system has much better performance in terms of accuracy, efficiency and robustness for the simultaneous localization and mapping (SLAM). As a critical component of multiple-robot SLAM, the problem of map merging still remains a challenge. To this end, this article casts it into point set registration problem and proposes an effective map merging method based on the context-based descriptors and correspondence expansion. It first extracts interest

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DENTSORAS, A. J. "Information generation during design: Information importance and design effort." Artificial Intelligence for Engineering Design, Analysis and Manufacturing 19, no. 1 (2005): 19–32. http://dx.doi.org/10.1017/s089006040505002x.

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The present paper studies the process of information generation during design and focuses on the relationship between the information importance and the required effort for its generation. Multiple associative relationships among design entities (handled as design descriptors) are used to represent the design knowledge. The characteristics of the dependent and the primary descriptors are examined and their distinct roles in the design process are discussed. Term definitions concerning the information importance and the design effort are also introduced. The descriptors are used to form a matri

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Desai, Alok, and Dah-Jye Lee. "Visual Odometry Drift Reduction Using SYBA Descriptor and Feature Transformation." IEEE Transactions on Intelligent Transportation Systems 17, no. 7 (2016): 1839–51. http://dx.doi.org/10.1109/tits.2015.2511453.

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Wei, Xiu-Shen, Chen-Lin Zhang, Jianxin Wu, Chunhua Shen, and Zhi-Hua Zhou. "Unsupervised object discovery and co-localization by deep descriptor transformation." Pattern Recognition 88 (April 2019): 113–26. http://dx.doi.org/10.1016/j.patcog.2018.10.022.

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Zhan, Jiang Han, Jing Ma, Jin Hao, and Jian Ding. "Full-Order Filters and Smoothers for Descriptor Systems with Delayed Measurements." Advanced Materials Research 571 (September 2012): 559–63. http://dx.doi.org/10.4028/www.scientific.net/amr.571.559.

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This paper is concerned with the filtering problem for descriptor system with measurement delays. Using full-order transformation, the original descriptor system with delayed measurements is transferred to the normal system with delayed state and delayed measurements. Based on the projection theory, the filter and smoother of the normal system are derived. Then, the full-order filter and smoother of the original descriptor system are given. The proposed estimators avoid the high-dimensional computation from state augmentation. Simulation research verifies the effectiveness of the proposed algo

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Qu, Xiujie, Fei Zhao, Mengzhe Zhou, and Haili Huo. "A Novel Fast and Robust Binary Affine Invariant Descriptor for Image Matching." Mathematical Problems in Engineering 2014 (2014): 1–7. http://dx.doi.org/10.1155/2014/129230.

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As the current binary descriptors have disadvantages of high computational complexity, no affine invariance, and the high false matching rate with viewpoint changes, a new binary affine invariant descriptor, called BAND, is proposed. Different from other descriptors, BAND has an irregular pattern, which is based on local affine invariant region surrounding a feature point, and it has five orientations, which are obtained by LBP effectively. Ultimately, a 256 bits binary string is computed by simple random sampling pattern. Experimental results demonstrate that BAND has a good matching result i

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Fan, Hongbiao, Min Meng, and Jun-e. Feng. "Observers of Fuzzy Descriptor Systems with Time-Delays." Abstract and Applied Analysis 2014 (2014): 1–9. http://dx.doi.org/10.1155/2014/714518.

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For discrete fuzzy descriptor systems with time-delays, the problem of designing fuzzy observers is investigated in this paper. Based on an equivalent transformation, discrete fuzzy descriptor systems with time-delays are converted into standard discrete systems with time-delays. Then, via linear matrix inequality (LMI) approach, both delay-dependent and delay-independent conditions for the existence of fuzzy state observers are obtained. Finally, two numerical examples are provided to illustrate the proposed method.

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Koliada, Myroslava O. "KY FAN NORM APPLICATION FOR VIDEO SEGMENTATION." Herald of Advanced Information Technology 3, no. 1 (2020): 345–51. http://dx.doi.org/10.15276/hait.01.2020.1.

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This article presents results of applying the KyFan norm in the context of solving the problem of video segmentation. Since the task of video analysis can be considered as analysis of the sequence of images, it was decided to find a way to formalize the description of the video frame using the mathematical apparatus of non-square matrices. When choosing a method, particular attention was paid precisely to universality with respect to the dimension of the initial data due to the technical characteristics and nature of the video data -video frames are matrices of arbitrary dimension. The ability

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Liu, Wei, and Zi Yun Lu. "The Asymptotical Stability Analysis for Switched Descriptor Systems." Applied Mechanics and Materials 29-32 (August 2010): 2150–56. http://dx.doi.org/10.4028/www.scientific.net/amm.29-32.2150.

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This paper is concerned with the asymptotical stability analysis for a class of switched uncertain descriptor systems with time-delay. The robustly asymptotical stability of this system is proven by making use of the generalized Lyapunov Stability theory, linear matrix inequality (LMI) tools and multiple Lyapunov function techniques. The conservation of result is greatly reduced by means of introducing the optimal weight matrix and avoiding vector matrix inequality in deducing procedure, in which there is no need of transformation and hypothesis for descriptor systems. The designed control law

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Zhao, Lidu, Zhongfu Xiang, Maolin Chen, et al. "Establishment and Extension of a Fast Descriptor for Point Cloud Registration." Remote Sensing 14, no. 17 (2022): 4346. http://dx.doi.org/10.3390/rs14174346.

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Point cloud registration (PCR) is a vital problem in remote sensing and computer vision, which has various important applications, such as 3D reconstruction, object recognition, and simultaneous localization and mapping (SLAM). Although scholars have investigated a variety of methods for PCR, the applications have been limited by low accuracy, high memory footprint, and slow speed, especially for dealing with a large number of point cloud data. To solve these problems, a novel local descriptor is proposed for efficient PCR. We formed a comprehensive description of local geometries with their s

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Zheng, Chengyong, Hong Li, and Guokuan Li. "Distance context based PCB film image alignment." Circuit World 40, no. 3 (2014): 110–18. http://dx.doi.org/10.1108/cw-03-2014-0006.

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Purpose – This paper presents a novel printed circuit board (PCB) film image alignment method based on distance context of image components, which can be directly used for PCB film inspection. PCB film inspection plays a very important role in PCB production. Design/methodology/approach – First, image components of reference film image and inspected film image are extracted. Then, local distance context (LDC) and global distance context (GDC) are computed for each image component. Using LDC and GDC, the similarity of each pair of components between the reference film image and the inspected fi

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Huang, Zeyi, Wenxiong Kang, Qiuxia Wu, and Xiaopeng Chen. "A new descriptor resistant to affine transformation and monotonic intensity change." Computer Vision and Image Understanding 120 (March 2014): 117–25. http://dx.doi.org/10.1016/j.cviu.2013.10.010.

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Ahmed, K. T., H. Afzal, S. Iqbal, M. G. Hussain, M. R. Mufti, and A. Karim. "Highly Efficient Multimedia Image Retrieval using Slim Descriptor." Nucleus 57, no. 4 (2021): 118–28. https://doi.org/10.71330/nucleus.57.04.1148.

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Efficient multimedia image extraction with high precision compatible with diverse image datasets is an implicit requirement of current image retrieval systems. In this paper, a multimedia image descriptor is introduced to achieve high performance along with high accuracy. For this, Histograms of Oriented Gradients (HOG) are extracted from a dense grid partitioned image by taking edge intensity based orientation histograms as primitive feature vectors. We depleted these massive redundant candidates to linearly uncorrelated variables by applying orthogonal transformation to achieve Principal Com

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Zhu, Zun Shang, Yue Qiang Zhang, Xiang Zhou, and Yang Shang. "An Affine SIFT Matching Algorithm Based on Local Patch Shape Estimation." Applied Mechanics and Materials 519-520 (February 2014): 553–56. http://dx.doi.org/10.4028/www.scientific.net/amm.519-520.553.

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In this paper we present an affine SIFT matching method to achieve reliable correspondence points in stereo matching with large viewpoint changes. We extended the affine invariant of the conventional SIFT approach by estimating the shape of the local patch around the interest point. Since we can obtain the scale information by SIFT detector, a second moment matrix (SMM) descriptor was employed to describe the shape. Furthermore, by comparing the shapes of the potential matches, we can normalize the template of SIFT descriptor and obtain the initial affine transformation. At last, we applied th

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Cao, Mengjuan, and Fucheng Liao. "Design of an Optimal Preview Controller for Linear Discrete-Time Descriptor Noncausal Multirate Systems." Scientific World Journal 2014 (2014): 1–11. http://dx.doi.org/10.1155/2014/965915.

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The linear discrete-time descriptor noncausal multirate system is considered for the presentation of a new design approach for optimal preview control. First, according to the characteristics of causal controllability and causal observability, the descriptor noncausal system is constructed into a descriptor causal closed-loop system. Second, by using the characteristics of the causal system and elementary transformation, the descriptor causal closed-loop system is transformed into a normal system. Then, taking advantage of the discrete lifting technique, the normal multirate system is converte

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Miciak, Mirosław. "Invariant Radon-Moment Descriptor for Postal Applications." Image Processing & Communications 20, no. 4 (2015): 13–21. http://dx.doi.org/10.1515/ipc-2015-0040.

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Abstract In this article a new solution of handwritten digits recognition system for postal applications is presented. Moreover, in this paper, a new approach of handwritten characters recognition was presented. The implemented algorithm is applied to recognition of postal items on the basis of postcode information. In connection with this article the research was carried with all digit characters used in authentic zip code of various mail pieces. Additionally, the paper contains some preliminary image processing for example normalization of the character. The main objective of this article is

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GENG, LICHUAN, SONGZHI SU, DONGLIN CAO, and SHAOZI LI. "PERSPECTIVE-INVARIANT IMAGE MATCHING FRAMEWORK WITH BINARY FEATURE DESCRIPTOR AND APSO." International Journal of Pattern Recognition and Artificial Intelligence 28, no. 08 (2014): 1455011. http://dx.doi.org/10.1142/s0218001414550118.

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A novel perspective invariant image matching framework is proposed in this paper, noted as Perspective-Invariant Binary Robust Independent Elementary Features (PBRIEF). First, we use the homographic transformation to simulate the distortion between two corresponding patches around the feature points. Then, binary descriptors are constructed by comparing the intensity of sample points surrounding the feature location. We transform the location of the sample points with simulated homographic matrices. This operation is to ensure that the intensities which we compared are the realistic correspond

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Babu, Eaby Kollonoor, Kamlesh Mistry, Muhammad Naveed Anwar, and Li Zhang. "Facial Feature Extraction Using a Symmetric Inline Matrix-LBP Variant for Emotion Recognition." Sensors 22, no. 22 (2022): 8635. http://dx.doi.org/10.3390/s22228635.

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With a large number of Local Binary Patterns (LBP) variants being currently used today, the significant and importance of visual descriptors in computer vision applications are prominent. This paper presents a novel visual descriptor, i.e., SIM-LBP. It employs a new matrix technique called the Symmetric Inline Matrix generator method, which acts as a new variant of LBP. The key feature that separates our variant from existing counterparts is that our variant is very efficient in extracting facial expression features like eyes, eye brows, nose and mouth in a wide range of lighting conditions. F

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Ajayi, Oluibukun Gbenga, and Ifeanyi Jonathan Nwadialor. "ACCURACY ASSESSMENT OF THE EFFECT OF DIFFERENT FEATURE DESCRIPTORS ON THE AUTOMATIC CO-REGISTRATION OF OVERLAPPING IMAGES." Geodesy and cartography 50, no. 1 (2024): 8–19. http://dx.doi.org/10.3846/gac.2024.18199.

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This research seeks to assess the effect of different selected feature descriptors on the accuracy of an automatic image registration scheme. Three different feature descriptors were selected based on their peculiar characteristics, and implemented in the process of developing the image registration scheme. These feature descriptors (Modified Harris and Stephens corner detector (MHCD), the Scale Invariant Feature Transform (SIFT) and the Speeded Up Robust Feature (SURF)) were used to automatically extract the conjugate points common to the overlapping image pairs used for the registration. Ran

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Wang, J. X., W. X. Wang, C. Y. Wang, H. Zhu, W. Y. He, and S. Y. Liu. "LINE SEGMENT MATCHING ALGORITHM BASED ON FEATURE GROUPING AND LBD DESCRIPTOR." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B2-2020 (August 12, 2020): 103–9. http://dx.doi.org/10.5194/isprs-archives-xliii-b2-2020-103-2020.

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Abstract. This paper proposes a line-matching algorithm based on feature grouping and a line band descriptor (LBD) to address the insufficient reliability of individual line descriptors for line matching. First, the algorithm generates line-pairs according to geometrical relationships such as the distances and angles between line segments extracted from a single image. Subsequently, the algorithm employs the epipolar line of intersection between two lines in a reference line-pair to constrain candidate pairs corresponding to the reference line-pair. Thereafter, each line in the reference line-

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Zhang, Lei, Jiexin Pu, Gui Chen, and Xiaoli Song. "An Improved SURF and Modified Zernike Moments Descriptor for Object Recognition." Electronics 14, no. 5 (2025): 1025. https://doi.org/10.3390/electronics14051025.

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Because single local or global characteristics can only depict the classification information of an object unilaterally or partially, that may result in low recognition accuracy; in this paper we propose an improved SURF and modified Zernike moments descriptor (ISMZMD) for object recognition. Firstly, we extracted the improved SURF and seven modified Zernike moments descriptors of objects. Secondly, we effectively fused the two features together with different weight factors based on their contribution to object identification. Thirdly, we computed the Euclidean distance to decide the recognit

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Oad, Ammar, Karishma Kumari, Imtiaz Hussain, Feng Dong, Bacha Hammad, and Rajkumari Oad. "Performance comparison of ORB, SURF and SIFT using Intracranial Haemorrhage CTScan Brain images." International Journal of Artificial Intelligence & Mathematical Sciences 1, no. 2 (2023): 26–34. http://dx.doi.org/10.58921/ijaims.v1i2.41.

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Medical images are crucial for both the doctor's accurate diagnosis and the patient's subsequent therapy. It is feasible to swiftly identify lesions in medical photos by using clever algorithms, and it is crucial to extract information from images. Feature extraction is an important step in image classification. It allows the representation of the content of images as perfectly as possible. The intention of this study is to certain overall performance assessment among the feature detector and the descriptor method, especially while there are numerous combos for assessment. Three techniques wer

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Huang, R., W. Yao, Z. Ye, Y. Xu, and U. Stilla. "RIDF: A ROBUST ROTATION-INVARIANT DESCRIPTOR FOR 3D POINT CLOUD REGISTRATION IN THE FREQUENCY DOMAIN." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences V-2-2020 (August 3, 2020): 235–42. http://dx.doi.org/10.5194/isprs-annals-v-2-2020-235-2020.

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Abstract. Registration of point clouds is a fundamental problem in the community of photogrammetry and 3D computer vision. Generally, point cloud registration consists of two steps: the search of correspondences and the estimation of transformation parameters. However, to find correspondences from point clouds, generating robust and discriminative features is of necessity. In this paper, we address the problem of extracting robust rotation-invariant features for fast coarse registration of point clouds under the assumption that the pairwise point clouds are transformed with rigid transformatio

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Li, Yongfei, Shicheng Wang, Hao He, Deyu Meng, and Dongfang Yang. "Fast Aerial Image Geolocalization Using the Projective-Invariant Contour Feature." Remote Sensing 13, no. 3 (2021): 490. http://dx.doi.org/10.3390/rs13030490.

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We address the problem of aerial image geolocalization over an area as large as a whole city through road network matching, which is modeled as a 2D point set registration problem under the 2D projective transformation and solved in a two-stage manner. In the first stage, all the potential transformations aligning the query road point set to the reference road point set are found by local point feature matching. A local geometric feature, called the Projective-Invariant Contour Feature (PICF), which consists of a road intersection and the closest points to it in each direction, is specifically

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Posokina, Natalia, Ol'ga Bessarab, Olga Karastoyanova, and Nadezhda Korovkina. "THE DESCRIPTION-PROFILE METHOD APPLICATION FOR THE ORGANOLEPTIC ASSESSMENT OF THE STORAGE CAPABILITY OF AGARICUS BISPORUS MUSHROOMS." Bulletin of KSAU, no. 7 (January 29, 2025): 154–63. https://doi.org/10.36718/1819-4036-2023-7-154-163.

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The purpose of the study is to develop a system of criteria for evaluating cultivated champignon (Agaricus bisporus) to determine the shelf life, during which the optimal level of sensory characteristics is maintained. Tasks: to formulate criteria characterizing the change in the quality level of champignons during storage; explore the dynamics of the selected criteria during storage to confirm their applicability. The objects of study were fresh cultivated champignons Agaricus bisporus with unstained cap epithelium. Previously, we developed a descriptor model that includes a dictionary of des

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Kaczorek, Tadeusz. "Analysis of the descriptor Roesser model with the use of the Drazin inverse." International Journal of Applied Mathematics and Computer Science 25, no. 3 (2015): 539–46. http://dx.doi.org/10.1515/amcs-2015-0040.

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AbstractA method of analysis for a class of descriptor 2D discrete-time linear systems described by the Roesser model with a regular pencil is proposed. The method is based on the transformation of the model to a special form with the use of elementary row and column operations and on the application of a Drazin inverse of matrices to handle the model. The method is illustrated with a numerical example

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Wu, Xian, Xueyi Guo, Hang Peng, Bin Su, Sabbir Ahamod, and Fenglin Han. "Corrupted Point Cloud Classification Through Deep Learning with Local Feature Descriptor." Sensors 24, no. 23 (2024): 7749. https://doi.org/10.3390/s24237749.

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Three-dimensional point cloud recognition is a very fundamental work in fields such as autonomous driving and face recognition. However, in real industrial scenarios, input point cloud data are often accompanied by factors such as occlusion, rotation, and noise. These factors make it challenging to apply existing point cloud classification algorithms in real industrial scenarios. Currently, most studies enhance model robustness from the perspective of neural network structure. However, researchers have found that simply adjusting the neural network structure has proven insufficient in addressi

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Naurin, Afrin, and Lai Wei. "Effective Interest Region Estimation Model to Represent Corners for Image." Signal & Image Processing: An International Journal (SIPIJ) 9, no. 6 (2019): 29–38. https://doi.org/10.5281/zenodo.2564897.

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One of the most important steps to describe local features is to estimate the interest region around the feature location to achieve the invariance against different image transformation. The pixels inside the interest region are used to build the descriptor, to represent a feature. Estimating the interest region around a corner location is a fundamental step to describe the corner feature. But the process is challenging under different image conditions. Most of the corner detectors derive appropriate scales to estimate the region to build descriptors. In our approach, we have proposed a new l

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Naurin, Afrin, and Lai Wei. "Effective Interest Region Estimation Model to Represent Corners for Image." Signal & Image Processing: An International Journal (SIPIJ) 9, no. 6 (2019): 29–38. https://doi.org/10.5281/zenodo.3445795.

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One of the most important steps to describe local features is to estimate the interest region around the feature location to achieve the invariance against different image transformation. The pixels inside the interest region are used to build the descriptor, to represent a feature. Estimating the interest region around a corner location is a fundamental step to describe the corner feature. But the process is challenging under different image conditions. Most of the corner detectors derive appropriate scales to estimate the region to build descriptors. In our approach, we have proposed a new l

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Jia, Chen, Fucheng Liao, and Jiamei Deng. "Impulse Elimination and Fault-Tolerant Preview Controller Design for a Class of Descriptor Systems." Mathematical Problems in Engineering 2019 (December 24, 2019): 1–13. http://dx.doi.org/10.1155/2019/3857275.

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In this paper, a fault-tolerant preview controller is designed for a class of impulse controllable continuous time descriptor systems with sensor faults. Firstly, the impulse is eliminated by introducing state prefeedback; then an algebraic equation and a normal control system are obtained by restricted equivalent transformation for the descriptor system after impulse elimination. Next, the model following problem in fault-tolerant control is transformed into the optimal regulation problem of the augmented system which is constructed by a general method. And the final augmented system and its

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Francisco, Amyr Edmar, Angelo Lance Seraspi, Jamillah Guialil, and Khatalyn Mata. "An enhancement of the Eigenface algorithm using weber local descriptor applied in attendance management system." International Student Research Review 2, no. 1 (2025): 139–73. https://doi.org/10.53378/isrr.164.

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This study presents an improved face recognition system tackling the Eigenface algorithm's limitations regarding lighting variance, class separability, and classification. The proposed method incorporates Weber Local Descriptor (WLD) for illumination normalization during training and recognition. Further improvements include Kernel Principal Component Analysis (KPCA) for non-linear feature transformation, Linear Discriminant Analysis (LDA) to maximize class separability, and Ridge classification for noise-resistant recognition, replacing Euclidean distance. Testing on the extended Yale B datas

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Berenguer Fernández, Yerai. "Robot navigation in dynamic environments using global-appearance descriptors. State of the art." Revista Doctorado UMH 2, no. 1 (2015): 2. http://dx.doi.org/10.21134/doctumh.v1i1.662.

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Map building and localization are two impor- tant abilities that autonomous mobile robots must develop. This way, much research has been carried out on these topics, and researchers have proposed many approaches to address these problems. This work presents a state of the art report on map building and localization using global appearance descriptors. In this approach, robots capture visual information from the environment and obtain, usually by means of a transformation, a global appearance descriptor for each image. Using these descriptors, the robot is able to estimate its location in a map

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Wang, Yan Wei, Si Qing Zhang, Bing Lin, Hong Liang, and Yan Ming Pan. "Feature Point Extraction Method of X-Ray Image Based on Scale Invariant." Applied Mechanics and Materials 274 (January 2013): 667–70. http://dx.doi.org/10.4028/www.scientific.net/amm.274.667.

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Feature Point Extraction Method of X-ray Image Based on Scale Invariant is proposed in this paper for industrial X-ray image with low contrast and some artifacts. First of all, the scale transformation of original image is adopted by the Gaussian kernel to building the DOG multi-scale pyramid. Then, the location and scale of the key points is fixed by the three-dimensional quadratic function. Finally, the Simply SIFT descriptor illustrates the key points. Experimental results show that the algorithm has good stability in translation, rotation and affine transformation, especially with 10 perce

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