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Journal articles on the topic 'Binary projection'

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Author: Grafiati

Published: 10 December 2022

Last updated: 28 January 2023

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1

ZHAO, JIAN, and JIAN AN. "AN ITERATIVE CONVEX HULL APPROACH FOR IMAGE SEGMENTATION AND CONTOUR EXTRACTION." International Journal of Pattern Recognition and Artificial Intelligence 26, no. 07 (November 2012): 1255013. http://dx.doi.org/10.1142/s0218001412550130.

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The contours and segments of objects in digital images have many important applications. Contour extractions of gray images can be converted into contour extractions of binary images. This paper presents a novel contour-extraction algorithm for binary images and provides a deduction theory for this algorithm. First, we discuss the method used to construct convex hulls of regions of objects. The contour of an object evolves from a convex polygon until the exact boundary is obtained. Second, the projection methods from lines to objects are studied, in which, a polygon iteration method is presented using linear projection. The result of the iteration is the contour of the object region. Lastly, addressing the problem that direct projections probably cannot find correct projection points, an effective discrete ray-projection method is presented. Comparisons with other contour deformation algorithms show that the algorithm in the present paper is very robust with respect to the shapes of the object regions. Numerical tests show that time consumption is primarily concentrated on convex hull computation, and the implementation efficiency of the program can satisfy the requirement of interactive operations.

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2

TANG, Peikai, Wei CHEN, and Yicheng MAI. "Binary projection for image local descriptor." Journal of Computer Applications 33, no. 4 (October 11, 2013): 1096–99. http://dx.doi.org/10.3724/sp.j.1087.2013.01096.

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3

Bleichrodt, Folkert, Jan De Beenhouwer, Jan Sijbers, and Kees Joost Batenburg. "Aligning Projection Images from Binary Volumes." Fundamenta Informaticae 135, no. 1-2 (2014): 21–42. http://dx.doi.org/10.3233/fi-2014-1110.

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4

Varga, László, Péter Balázs, and Antal Nagy. "Projection Selection Dependency in Binary Tomography." Acta Cybernetica 20, no. 1 (2011): 167–87. http://dx.doi.org/10.14232/actacyb.20.1.2011.12.

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5

Delhomm�, C. "Projection properties and reflexive binary relations." Algebra Universalis 41, no. 4 (September 1, 1999): 255–81. http://dx.doi.org/10.1007/s000120050115.

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6

Yan, Hui, Xiaotong Yuan, Shuicheng Yan, and Jingyu Yang. "Correntropy based feature selection using binary projection." Pattern Recognition 44, no. 12 (December 2011): 2834–42. http://dx.doi.org/10.1016/j.patcog.2011.04.014.

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7

KUMAR, CHANDAN. "NP/DP Parameter and Classifier Languages: A Case of Magahi." Journal of Indian and Asian Studies 01, no. 01 (January 2020): 2050005. http://dx.doi.org/10.1142/s2717541320500059.

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The paper presents the structural evidence for the existence of DP in the article-less language, Magahi. Article-less languages can be divided into two types: class languages and non-class languages. Most of the debate surrounding the treatment of article-less languages as DP/NP languages see only the binary distinction (article and non-article languages). In this paper, it is argued that the class-languages present richer structural evidences for the presence of the functional projection above NP. Along with presenting few structural evidences against the generalization presented by Bošković (2005), language-independent motivation for the functional projection like DP is also discussed. It is also argued that merit of the projection of the DP is also semantically justified. The argument that there can be various functional projections in the extended projection of NP weakens the strongest claim that article-less languages lack DP.

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8

Fu Lina, 付莉娜, 杨静雯 Yang Jingwen, 李雁玲 Li Yanling, 张宗华 Zhang Zonghua, 高楠 Gao Nan, 孟召宗 Meng Zhaozong, 高峰 Gao Feng, and 蒋向前 Jiang Xiangqian. "二值条纹离焦投影技术综述." Laser & Optoelectronics Progress 59, no. 14 (2022): 1415011. http://dx.doi.org/10.3788/lop202259.1415011.

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9

Weng, Zhenyu, and Yuesheng Zhu. "Online Hashing with Efficient Updating of Binary Codes." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 07 (April 3, 2020): 12354–61. http://dx.doi.org/10.1609/aaai.v34i07.6920.

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Online hashing methods are efficient in learning the hash functions from the streaming data. However, when the hash functions change, the binary codes for the database have to be recomputed to guarantee the retrieval accuracy. Recomputing the binary codes by accumulating the whole database brings a timeliness challenge to the online retrieval process. In this paper, we propose a novel online hashing framework to update the binary codes efficiently without accumulating the whole database. In our framework, the hash functions are fixed and the projection functions are introduced to learn online from the streaming data. Therefore, inefficient updating of the binary codes by accumulating the whole database can be transformed to efficient updating of the binary codes by projecting the binary codes into another binary space. The queries and the binary code database are projected asymmetrically to further improve the retrieval accuracy. The experiments on two multi-label image databases demonstrate the effectiveness and the efficiency of our method for multi-label image retrieval.

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10

Fu, Guangkai, Yiping Cao, Yapin Wang, Yingying Wan, Lu Wang, and Chengmeng Li. "Three-dimensional shape measurement based on binary fringe conventional projection." Transactions of the Institute of Measurement and Control 41, no. 14 (May 17, 2019): 4073–83. http://dx.doi.org/10.1177/0142331219848029.

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A three-dimensional (3D) shape measurement method based on binary fringe conventional projection is proposed. In traditional 3D shape measurement methods based on binary fringe projection, the binary fringe is used as an approximate sinusoidal fringe by defocusing projection or even directly used as an approximate sinusoidal fringe by nonlinear error suppression feature of large-step phase measuring profilometry (PMP). In the proposed method (Prop), neither defocusing projection is needed nor large-step PMP must be used. When the binary fringe is conventionally projected on the measured object, just by filtering operation in spatial frequency domain from the captured deformed pattern, the nearly unbroken sinusoidal deformed pattern can be extracted efficiently. While N ( N≥3) frames binary fringes with 1/ N period misalignment between each adjacent fringe are conventionally projected onto the measured object sequentially, the corresponding nearly unbroken N-step sinusoidal deformed patterns extracted from the N frames captured deformed patterns can be used to reconstruct the 3D shape of the measured object with N-step PMP algorithm. The experimental results show the feasibility and validity of the Prop. It is more flexible for its optional fringe period and optional phase-shifting steps. It has potential application in the real-time 3D shape measurement.

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11

Wang, Ying, Yanlong Zhao, and Ji-Feng Zhang. "Distributed Recursive Projection Identification with Binary-Valued Observations." Journal of Systems Science and Complexity 34, no. 5 (October 2021): 2048–68. http://dx.doi.org/10.1007/s11424-021-1267-x.

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12

Lékó, Gábor, and Péter Balázs. "Scale Invariance in Projection Selection Using Binary Tomography." Fundamenta Informaticae 172, no. 2 (February 8, 2020): 129–42. http://dx.doi.org/10.3233/fi-2020-1897.

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13

Fu, Yanjun, Zhigang Wang, Jie Yang, and Guangyu Jiang. "Period correction method for binary fringe defocused projection." Optik 125, no. 22 (November 2014): 6722–26. http://dx.doi.org/10.1016/j.ijleo.2014.08.069.

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14

Jadda, Zoubida, Patrice Parraud, and Soukayna Qarboua. "Quaternary cryptographic bent functions and their binary projection." Cryptography and Communications 5, no. 1 (November 30, 2012): 49–65. http://dx.doi.org/10.1007/s12095-012-0077-3.

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15

Wang Fei, 王飞, 蔡家旭 Cai Jiaxu, 潘艳娟 Pan Yanjuan, 奚冬冬 Xi Dongdong, 王玉伟 Wang Yuwei, and 刘路 Liu Lu. "二值条纹投影伪装物体检测技术." Acta Optica Sinica 41, no. 16 (2021): 1612005. http://dx.doi.org/10.3788/aos202141.1612005.

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16

JIE, ZHANG, PAN RURU, and GAO WEIDONG. "A backlighting method for accurate inspection of woven fabric density." Industria Textila 68, no. 01 (March 1, 2017): 31–36. http://dx.doi.org/10.35530/it.068.01.1321.

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To inspect the yarn-dyed fabric density automatically, an efficient backlighting method is proposed in this paper. This method consists of four steps: fabric image acquisition, yarn skew detection, image threshold segmentation and binary image projection. Firstly, it is utilized an imaging acquisition system with two reflective and transmission lights in its top and bottom placements, and the reflective and transmission images of the same region in the fabric are captured respectively by adjusting the illumination condition. Secondly, the skew angles of yarns in transmission image are obtained by using Hough transform to inspect them in reflective image. Then, the transmission fabric image is converted into binary image by Otsu algorithm. Finally, the projection curves produced from the binary image by the projection method are smoothed by the locally weighted regression algorithm. The number of peaks in the projection curve is counted and therefore the number of yarns is detected and the density is calculated precisely. The experimental results proved that the proposed method is effective for woven fabrics by testing eight grey and color fabric samples with different weave patterns.

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17

Silva, Jadiel C., Fernando P. A. Lima, Anna Diva P. Lotufo, and Jorge M. M. C. P. Batista. "Artificial Immune System with Negative Selection Applied to Facial Biometry Based on Binary Pattern Characteristics." International Journal on Artificial Intelligence Tools 28, no. 01 (February 2019): 1950005. http://dx.doi.org/10.1142/s0218213019500052.

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This work aims to explore resources and alternatives for 3D facial biometry using Binary Patterns. A 3D facial geometry image is converted into two 2D representations, appointed as descriptors: A Depth Map and an Azimuthal Projection Distance Image. The first is known as traditional facial geometry, and the second is normal facial geometry that is able to capture the information of different geometries. The characteristics of Local Binary Patterns, Local Phase Quantisers and Gabor Binary Patterns were used with the Depth Map and Azimuthal Projection Distance Image to produce six new facial descriptors: 3D Local Binary Patterns, Local Azimuthal Binary Patterns, Local Depth Phase Quantisers, Local Azimuthal Phase Patterns, and Local Depth Gabor Binary Pattern Magnitudes and Phases. Then, this work uses the immune concept to propose a new approach to realize facial biometry, where the eight new facial descriptors were applied to an Artificial Intelligence algorithm named Artificial Immune Systems of Negative Selection. The analysis of the results shows the efficiency, robustness, precision and reliability of this approach, encouraging further research in this area.

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18

ZOU Yu, 邹瑜, 梁斌 LIANG Bin, 王学谦 WANG Xue-qian, 张涛 ZHANG Tao, and 宋靖雁 SONG Jing-yan. "Spacetarget pose estimation based on binary rotational projection histogram." Optics and Precision Engineering 25, no. 11 (2017): 2958–67. http://dx.doi.org/10.3788/ope.20172511.2958.

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19

Garnica, G., M. Padilla, and M. Servin. "Dual-sensitivity profilometry with defocused projection of binary fringes." Applied Optics 56, no. 28 (September 29, 2017): 7985. http://dx.doi.org/10.1364/ao.56.007985.

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20

Carpy, Sabrina, and Hélène Mathis. "Modeling binary alloy solidification by a random projection method." Numerical Methods for Partial Differential Equations 35, no. 2 (December 17, 2018): 733–60. http://dx.doi.org/10.1002/num.22322.

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21

al-Rifaie, Mohammad Majid, and Tim Blackwell. "Reduced projection angles for binary tomography with particle aggregation." Evolutionary Intelligence 9, no. 3 (August 8, 2016): 67–79. http://dx.doi.org/10.1007/s12065-016-0140-7.

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22

Fortes, W., and K. J. Batenburg. "Quality bounds for binary tomography with arbitrary projection matrices." Discrete Applied Mathematics 183 (March 2015): 42–58. http://dx.doi.org/10.1016/j.dam.2014.01.026.

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23

CHENG, JUN, RONALD CHUNG, EDMUND Y. LAM, KENNETH S. M. FUNG, and YANGSHENG XU. "OPTIMIZATION OF BIT-PAIRING CODIFICATION WITH LEARNING FOR 3D RECONSTRUCTION." International Journal of Image and Graphics 07, no. 03 (July 2007): 445–62. http://dx.doi.org/10.1142/s0219467807002763.

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Coded structured light is an active approach that obtains the shape of object. In our previous work, we proposed a new binary projection mechanism for inspecting semiconductor products. The mechanism consists of only a single light source in combination with a binary grating for projecting binary pattern. By shifting the binary grating in space and in every shifting taking a separate image of the illuminated surface, each position on the illuminated surface is attached with a unique binary string for correspondence. In the mechanism the inspection speed is governed by the number of needed images which also equals to the number of shiftings of the grating. To reduce image number, we propose that two neighbor bits are combined together to produce unique codeword, which is referred to as bit-pairing mechanism. This paper addresses how the spatial shifting of bit-pairing mechanism can be designed optimally for minimizing this number for faster inspection speed. An optimal solution to shifting strategy optimization is proposed that is applicable to any given binary patterns. Theoretical analysis and real image experiments are presented to illustrate the workability of the solutions.

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24

Hussain, Abid, Heng-Chao Li, Muqadar Ali, Samad Wali, Mehboob Hussain, and Amir Rehman. "An Efficient Supervised Deep Hashing Method for Image Retrieval." Entropy 24, no. 10 (October 7, 2022): 1425. http://dx.doi.org/10.3390/e24101425.

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In recent years, searching and retrieving relevant images from large databases has become an emerging challenge for the researcher. Hashing methods that mapped raw data into a short binary code have attracted increasing attention from the researcher. Most existing hashing approaches map samples to a binary vector via a single linear projection, which restricts the flexibility of those methods and leads to optimization problems. We introduce a CNN-based hashing method that uses multiple nonlinear projections to produce additional short-bit binary code to tackle this issue. Further, an end-to-end hashing system is accomplished using a convolutional neural network. Also, we design a loss function that aims to maintain the similarity between images and minimize the quantization error by providing a uniform distribution of the hash bits to illustrate the proposed technique’s effectiveness and significance. Extensive experiments conducted on various datasets demonstrate the superiority of the proposed method in comparison with state-of-the-art deep hashing methods.

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25

Reza, Feishal, Panca Mudjirahardjo, and Erni Yudaningtyas. "Designing an Optimization System Toward Moving Object Projection in 3-Dimensional Space Using Genetic Algorithm." JURNAL INFOTEL 10, no. 4 (November 30, 2018): 186. http://dx.doi.org/10.20895/infotel.v10i4.408.

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This research offers a scheme system toward moving object projection in 3-dimensional space that using Stereo Vision Camera. The system benefits in giving an alternative solution in projecting practically without manual identification by conventional measuring device. The result of the projection in the system is in the form of coordinate position information (x, y, z), the length, the width, and the height of the object detected. The output will be displayed in the real-time digital image with 3-dimensional modeling. In the process of the object identification, there is a stage when an image is converted from colored image to binary image. But the conversion uses the threshold method which is considered less efficient when an object moves. As consequence, the new adaptive method in solving the problem is needed. Genetic Algorithm is proposed as the optimization method because it is considered suitable with the emerging problems. In the optimization process, genetic algorithm is in a task of searching process and determining the threshold value as the process of creating binary image. The result shows an increased accuracy in the identification process after the system is optimized by the Genetic Algorithm (GA).

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26

Punithavathi, P., and S. Geetha. "Random Projection-based Cancelable Template Generation for Sparsely Distributed Biometric Patterns." Indonesian Journal of Electrical Engineering and Computer Science 7, no. 3 (September 1, 2017): 877. http://dx.doi.org/10.11591/ijeecs.v7.i3.pp877-886.

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Cancelable biometrics, a template transformation approach, attempts to provide robustness for authentication services based on biometrics. Several biometric template protection techniques represent the biometric information in binary form as it provides benefits in matching and storage. In this context, it becomes clear that often such transformed binary representations can be easily compromised and breached. In this paper, we propose an efficient non-invertible template transformation approach using random projection technique and Discrete Fourier transformation to shield the binary biometric representations. The cancelable fingerprint templates designed by the proposed technique meets the requirements of revocability, diversity, non-invertibility and performance. The matching performance of the cancelable fingerprint templates generated using proposed technique, have improved when compared with the state-of-art methods.

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27

Yan Fei, 严飞, 祁健 Qi Jian, 刘银萍 Liu Yinping, 吴迪 Wu Di, and 刘佳 Liu Jia. "一种二值编码条纹聚焦投影的三维测量方法." Acta Optica Sinica 42, no. 22 (2022): 2212002. http://dx.doi.org/10.3788/aos202242.2212002.

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28

Bieberle, M., and U. Hampel. "Level-set reconstruction algorithm for ultrafast limited-angle X-ray computed tomography of two-phase flows." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 373, no. 2043 (June 13, 2015): 20140395. http://dx.doi.org/10.1098/rsta.2014.0395.

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Tomographic image reconstruction is based on recovering an object distribution from its projections, which have been acquired from all angular views around the object. If the angular range is limited to less than 180° of parallel projections, typical reconstruction artefacts arise when using standard algorithms. To compensate for this, specialized algorithms using a priori information about the object need to be applied. The application behind this work is ultrafast limited-angle X-ray computed tomography of two-phase flows. Here, only a binary distribution of the two phases needs to be reconstructed, which reduces the complexity of the inverse problem. To solve it, a new reconstruction algorithm (LSR) based on the level-set method is proposed. It includes one force function term accounting for matching the projection data and one incorporating a curvature-dependent smoothing of the phase boundary. The algorithm has been validated using simulated as well as measured projections of known structures, and its performance has been compared to the algebraic reconstruction technique and a binary derivative of it. The validation as well as the application of the level-set reconstruction on a dynamic two-phase flow demonstrated its applicability and its advantages over other reconstruction algorithms.

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29

Xiaofeng Fu, 付晓峰, and 韦巍 Wei Wei. "Multi-radius centralized binary pattern histogram projection for face recognition." Chinese Optics Letters 7, no. 6 (2009): 475–78. http://dx.doi.org/10.3788/col20090706.0475.

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30

Chee, Kong-Yik, Zhe Jin, Danwei Cai, Ming Li, Wun-She Yap, Yen-Lung Lai, and Bok-Min Goi. "Cancellable speech template via random binary orthogonal matrices projection hashing." Pattern Recognition 76 (April 2018): 273–87. http://dx.doi.org/10.1016/j.patcog.2017.10.041.

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31

Chen, Sugen, Xiaojun Wu, and Hefeng Yin. "A novel projection twin support vector machine for binary classification." Soft Computing 23, no. 2 (December 11, 2017): 655–68. http://dx.doi.org/10.1007/s00500-017-2974-z.

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32

He, Xiaoyu, Dongliang Zheng, Qian Kemao, and George Christopoulos. "Quaternary gray-code phase unwrapping for binary fringe projection profilometry." Optics and Lasers in Engineering 121 (October 2019): 358–68. http://dx.doi.org/10.1016/j.optlaseng.2019.04.009.

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33

Lee, Jimmy, and K. Leung. "A Stronger Consistency for Soft Global Constraints in Weighted Constraint Satisfaction." Proceedings of the AAAI Conference on Artificial Intelligence 24, no. 1 (July 3, 2010): 121–27. http://dx.doi.org/10.1609/aaai.v24i1.7550.

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Weighted Constraint Satisfaction is made practical by powerful consistency techniques, such as AC*, FDAC* and EDAC*, which reduce search space effectively and efficiently during search, but they are designed for only binary and ternary constraints. To allow soft global constraints, usually of high arity, to enjoy the same benefits, Lee and Leung give polynomial time algorithms to enforce generalized AC* (GAC*) and FDAC* (FDGAC*) for projection-safe soft non-binary constraints. Generalizing the stronger EDAC* is less straightforward. In this paper, we first reveal the oscillation problem when enforcing EDAC* on constraints sharing more than one variable. To avoid oscillation, we propose a weak version of EDAC* and generalize it to weak EDGAC* for non-binary constraints. Weak EDGAC* is stronger than FDGAC* and GAC*, but weaker than VAC and soft k-consistency for k > 2. We also show that weak EDGAC* can be enforced in polynomial time for projection-safe constraints. Extensive experimentation confirms the efficiency of our proposal.

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34

Bakhtiyarly, Ikhtiyar Bahram oglu, Ruksana Jalal kizi Kurbanova, Shahri Seyfaly kizi Abdullaeva, Ziyafat Mamed kizi Mukhtarova, and Fatmahanum Mamed Mammadova. "Liquidus surface of the quasi-ternary system Cu2S–In2S3–FeS." Kondensirovannye sredy i mezhfaznye granitsy = Condensed Matter and Interphases 23, no. 1 (March 16, 2021): 16–24. http://dx.doi.org/10.17308/kcmf.2021.23/3293.

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A projection of the liquidus surface of the quasi-ternary system Cu2S-In2S3-FeS was constructed as a result of experimental studies of quasi-binary and non-quasi-binary sections and based on the data on binary systems comprising a ternary system.Each section (six quasi-binary and four non-quasi-binary ones) was studied separately using complex methods of physicochemical analysis: differential thermal analysis, X-ray phase analysis, and microstructural analysis.It was found that the quasi-ternary system Cu2S-In2S3-FeS has six fields of primary crystallisation of separate phases and eleven monovariant equilibrium curves along which two phases are co-crystallised. Non-variant equilibrium points were obtained through the extrapolation of the direction of monovariant equilibrium curves.The quasi-ternary system Cu2S-In2S3-FeS is characterised by 17 non-variant equilibrium points, where Е1-Е5 are triple eutectic points.The projection diagram of the liquidus surface is characterised by three crystallisation fields of the initial componets (Cu2S, In2S3, FeS), four fields of binary compounds, and one field of a complex compound (CuFeIn3S6).Since complete solubility of the initial components in liquid and solid states is observed in the quasi-binary section CuIn5S8‑FeIn2S4, the fields of primary crystallisation of CuIn5S8 and FeIn2S4 are absent; they are replaced by an unlimited solid solution based on these components.The fields of primary crystallisation of Cu2S, FeS, and CuInS2 are the most extensive in the ternary system Cu2S-In2S3-FeS. The reactions occurring at monovariant equilibrium points are presented.

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Timonidis, Nestor, Rembrandt Bakker, and Paul Tiesinga. "Prediction of a Cell-Class-Specific Mouse Mesoconnectome Using Gene Expression Data." Neuroinformatics 18, no. 4 (May 24, 2020): 611–26. http://dx.doi.org/10.1007/s12021-020-09471-x.

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Abstract Reconstructing brain connectivity at sufficient resolution for computational models designed to study the biophysical mechanisms underlying cognitive processes is extremely challenging. For such a purpose, a mesoconnectome that includes laminar and cell-class specificity would be a major step forward. We analyzed the ability of gene expression patterns to predict cell-class and layer-specific projection patterns and assessed the functional annotations of the most predictive groups of genes. To achieve our goal we used publicly available volumetric gene expression and connectivity data and we trained computational models to learn and predict cell-class and layer-specific axonal projections using gene expression data. Predictions were done in two ways, namely predicting projection strengths using the expression of individual genes and using the co-expression of genes organized in spatial modules, as well as predicting binary forms of projection. For predicting the strength of projections, we found that ridge (L2-regularized) regression had the highest cross-validated accuracy with a median r2 score of 0.54 which corresponded for binarized predictions to a median area under the ROC value of 0.89. Next, we identified 200 spatial gene modules using a dictionary learning and sparse coding approach. We found that these modules yielded predictions of comparable accuracy, with a median r2 score of 0.51. Finally, a gene ontology enrichment analysis of the most predictive gene groups resulted in significant annotations related to postsynaptic function. Taken together, we have demonstrated a prediction workflow that can be used to perform multimodal data integration to improve the accuracy of the predicted mesoconnectome and support other neuroscience use cases.

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36

Yang, Chaozhi, Yiping Cao, and Xiuzhang Huang. "Single-Shot Phase Measuring Profilometry Based on Quaternary Grating Projection." Applied Sciences 11, no. 6 (March 12, 2021): 2536. http://dx.doi.org/10.3390/app11062536.

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In this paper, we propose a new single-shot three-dimensional (3D) measuring method based on quaternary grating projection. In traditional binary grating phase measuring profilometry (PMP), a multi-step or color fringe pattern are usually used to extract the sinusoidal fringes. In our proposed method, by using the DLP4500’s 2-bit gray coding mode, the grayscale is quaternary. The three non-zero grayscales cyclically arranged in equal width, and the fourth grey value is 0 which is not encoded in the fringe pattern but represents the shadow information in the deformed pattern, where a quaternary grating is encoded. When the DLP4500 projects the quaternary grating onto the measured object, the charge coupled device (CCD) captures the corresponding deformed pattern synchronously. Three frames of binary deformed patterns with 1/3 duty cycle and a relative displacement of 1/3 period can be decomposed by the segmentation algorithm proposed in this paper. Three sinusoidal deformed patterns with a 2π/3 shift-phase can be obtained by extracting the fundamental frequency of the three binary deformed patterns correspondingly, and the 3D shape of the object can be reconstructed by PMP. Experimental results show the effectiveness and feasibility of the proposed method. Because the DLP4500 only needs 2-bit coded grating for projection, the refresh rate of the projected grating is as high as 1428 Hz, which will have a broad application prospect in real time and fast online measurement.

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37

HOU, TUNG-HSU (TONY), and MING-DER PERN. "A SHAPE CLASSIFIER BY USING IMAGE PROJECTION AND A NEURAL NETWORK." International Journal of Pattern Recognition and Artificial Intelligence 14, no. 02 (March 2000): 225–42. http://dx.doi.org/10.1142/s0218001400000155.

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In this research a computer vision-based shape recognition system which combines an image projection and the back propagation neural network is proposed. The system uses the image projection and features of the projection histogram to represent the shape, and uses the back propagation neural network to classify the shape. In this research, a fast normalization scheme is developed which is especially designed for image projection and can also find the same projection axis no matter what the object's orientation. Therefore, the proposed system can be invariant to scale, translation, and orientation variations. This research finds that the direct representation scheme of the back propagation neural net has better accuracy than the binary coding representation scheme. This research also finds that the proposed system's classification accuracy is greater than 98.8% and its processing speed is also very fast. Therefore, the proposed system is feasible for use in shape classification, in practice.

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38

BALLICO, E., and A. BERNARDI. "MINIMAL DECOMPOSITION OF BINARY FORMS WITH RESPECT TO TANGENTIAL PROJECTIONS." Journal of Algebra and Its Applications 12, no. 06 (May 9, 2013): 1350010. http://dx.doi.org/10.1142/s0219498813500102.

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Let C ⊂ ℙn+1 be a rational normal curve and let X ⊂ ℙn be one of its tangential projection. We describe the X-rank of a point P ∈ ℙn in terms of the schemes evincing the C-rank or the border C-rank of the preimage of P.

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Zheng, Zhuojun, Jian Gao, Yizhong Zhuang, Lanyu Zhang, and Xin Chen. "High dynamic defocus response method for binary defocusing fringe projection profilometry." Optics Letters 46, no. 15 (July 29, 2021): 3749. http://dx.doi.org/10.1364/ol.432151.

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Pan, Jiahui. "Color-coded binary fringe projection technique for 3-D shape measurement." Optical Engineering 44, no. 2 (February 1, 2005): 023606. http://dx.doi.org/10.1117/1.1840973.

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Zhou, Pei, Jiangping Zhu, Xianyu Su, Hailong Jing, and Xing Zhang. "Three-dimensional shape measurement using color random binary encoding pattern projection." Optical Engineering 56, no. 10 (October 10, 2017): 1. http://dx.doi.org/10.1117/1.oe.56.10.104102.

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ITO, Ryosuke, Yuki MINAMI, Daisuke TANAKA, and Kenji SUGIMOTO. "Position Control Experiment of Mobile Robots by using Binary Image Projection." Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec) 2016 (2016): 2P2–04a3. http://dx.doi.org/10.1299/jsmermd.2016.2p2-04a3.

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Vardi, Eilat, Gabor T. Herman, and T. Yung Kong. "Speeding up stochastic reconstructions of binary images from limited projection directions." Linear Algebra and its Applications 339, no. 1-3 (December 2001): 75–89. http://dx.doi.org/10.1016/s0024-3795(01)00455-4.

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Landgraf, Andrew J., and Yoonkyung Lee. "Dimensionality reduction for binary data through the projection of natural parameters." Journal of Multivariate Analysis 180 (November 2020): 104668. http://dx.doi.org/10.1016/j.jmva.2020.104668.

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Van Mechelen, Even, and Paul De Boeck. "Projection of a binary criterion into a model of hierarchical classes." Psychometrika 55, no. 4 (December 1990): 677–94. http://dx.doi.org/10.1007/bf02294616.

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Guo, Jin, and Yanlong Zhao. "Recursive projection algorithm on FIR system identification with binary-valued observations." Automatica 49, no. 11 (November 2013): 3396–401. http://dx.doi.org/10.1016/j.automatica.2013.08.011.

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Heinbockel, T., T. A. Christensen, and J. G. Hildebrand. "Representation of binary pheromone blends by glomerulus-specific olfactory projection neurons." Journal of Comparative Physiology A 190, no. 12 (September 17, 2004): 1023–37. http://dx.doi.org/10.1007/s00359-004-0559-7.

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Lee, Yeunghak. "Two-wheelers Detection using Uniform Local Binary Pattern for Projection Vectors." Journal of Korea Multimedia Society 18, no. 4 (April 30, 2015): 443–51. http://dx.doi.org/10.9717/kmms.2015.18.4.443.

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Li, Xuexing, Miao Gong, Zhao Zhang, Zhijiang Zhang, and Chen Yang. "Calibration method for fringe projection profilometry with a binary defocusing technique." Optical Review 24, no. 4 (May 13, 2017): 495–504. http://dx.doi.org/10.1007/s10043-017-0340-0.

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Xu, Wei, Jian Xin Zhou, Sheng Yong Pang, Dun Ming Liao, and Ya Jun Yin. "Numerical Simulation of Macrosegregation Formation in Binary Alloy Solidification Processing Based on Modified Projection Method." Advanced Materials Research 314-316 (August 2011): 369–73. http://dx.doi.org/10.4028/www.scientific.net/amr.314-316.369.

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A simplified mathematical model for describing the solidification processing of fluid flow, heat and solute transfer in binary alloys is developed. The conservation equations are numerically solved on a staggered grid by using the control volume-based finite difference method. As the interdendritic flow in the mushy zone is governed by Darcy’s law, the Modified Projection Method is presented for solving the momentum and continuity equations. The solidification processing of Fe-C alloy in rectangular domains is simulated and discussed. The numerical result shows that, by using the Modified Projection Method technique, the presented model is able to predict the macrosegregation formation effectively.

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