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Journal articles on the topic 'Code recognition'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 May 2024

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1

Matthews, Brian W. "No code for recognition." Nature 335, no. 6188 (1988): 294–95. http://dx.doi.org/10.1038/335294a0.

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2

Wolfe, Scot A., Robert A. Grant, Monicia Elrod-Erickson, and Carl O. Pabo. "Beyond the “Recognition Code”." Structure 9, no. 8 (2001): 717–23. http://dx.doi.org/10.1016/s0969-2126(01)00632-3.

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3

Liu, Jie, Li Min Zhang, and Zhao Gen Zhong. "Blind Recognition of Recursive System Convolutional Codes." Applied Mechanics and Materials 631-632 (September 2014): 816–19. http://dx.doi.org/10.4028/www.scientific.net/amm.631-632.816.

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Recursive system convolutional codes (RSC codes) are the commonly used coding form for Turbo sub-encoders. For blind recognition problem of RSC codes, a novel method is proposed to recognize code parameters and generator polynomials. Firstly, code parameters are estimated by analyzing matrix constructed from the received codeword. Then, the mathematical model for recognition of generator polynomials is derived according to RSC codes’ characteristics, and the specific implementation steps are introduced. Finally, simulation results from Matlab show that the performance of the method is obviousl

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4

Huo, Lina, Jianxing Zhu, Pradeep Kumar Singh, and Pljonkin Anton Pavlovich. "Research on QR image code recognition system based on artificial intelligence algorithm." Journal of Intelligent Systems 30, no. 1 (2021): 855–67. http://dx.doi.org/10.1515/jisys-2020-0143.

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Abstract The QR code recognition often faces the challenges of uneven background fluctuations, inadequate illuminations, and distortions due to the improper image acquisition method. This makes the identification of QR codes difficult, and therefore, to deal with this problem, artificial intelligence-based systems came into existence. To improve the recognition rate of QR image codes, this article adopts an improved adaptive median filter algorithm and a QR code distortion correction method based on backpropagation (BP) neural networks. This combination of artificial intelligence algorithms is

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5

Kimura, F., and M. Shridhar. "Segmentation-recognition algorithm for zip code field recognition." Machine Vision and Applications 5, no. 3 (1992): 199–210. http://dx.doi.org/10.1007/bf02626998.

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6

HR, GITE, and MAHENDER CN. "IRIS CODE GENERATION AND RECOGNITION." International Journal of Machine Intelligence 3, no. 3 (2011): 103–7. http://dx.doi.org/10.9735/0975-2927.3.3.103-107.

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7

Kral, Andrej. "Temporal Code and Speech Recognition." Acta Oto-Laryngologica 120, no. 4 (2000): 529–30. http://dx.doi.org/10.1080/000164800750046045.

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8

Müller-Hill, Benno, and Peter Kolkhof. "DNA recognition and the code." Nature 369, no. 6482 (1994): 614. http://dx.doi.org/10.1038/369614a0.

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9

Fan, Di, Jia Li, Mao Yong Cao, Nong Liang Sun, and Hong Yu. "Recognizing Check Magnetic Code Based on Peak-Valley Code and Distance." Applied Mechanics and Materials 145 (December 2011): 588–92. http://dx.doi.org/10.4028/www.scientific.net/amm.145.588.

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The check is a popular form for the non-cash payment and accounts for more than 50% of the non-cash transactions. Magnetic ink character recognition system can recognize the check magnetic code automatically and get the information of the bank and account. In magnetic ink character recognition system, the recognizing algorithm is mostly based on correlation coefficient. The computational cost of this algorithm is very high. This paper has proposed a new algorithm based on the peak-valley code and peak-valley distance after analyzing the characteristics of magnetic code signals in E-13B standar

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10

Wang, Lan Xun, and Dan Fang Li. "A New Method for BCH Codes of Blind Recognition." Advanced Materials Research 631-632 (January 2013): 1403–8. http://dx.doi.org/10.4028/www.scientific.net/amr.631-632.1403.

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According to the invariance property of the BCH code and Euclidean algorithm to calculate the greatest common factor (GCF) between code group and its cyclic shift code group. There is a method by using the degree distribution probability sum function of the greatest common factor to recognize the code length of BCH code. On this basis, the GCF can be extracted of the greatest degree distribution probability from the sum function, with the generator polynomial obtained by decomposing the GCF. The simulation results show that this method can achieve the recognition probability above 95% with BER

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11

WANG, KONGQIAO, YANMING ZOU, and HAO WANG. "1D BAR CODE READING ON CAMERA PHONES." International Journal of Image and Graphics 07, no. 03 (2007): 529–50. http://dx.doi.org/10.1142/s0219467807002805.

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The availability of camera phones provides people with a mobile platform for decoding bar codes, whereas conventional scanners lack mobility. However, using a normal camera phone in such applications is challenging due to the out-of-focus problem. In this paper, we present the research effort on the bar code reading algorithms using a VGA camera phone, NOKIA 7650. EAN-13, a widely used 1D bar code standard, is taken as an example to show the efficiency of the method. A wavelet-based bar code region location and knowledge-based bar code segmentation scheme is applied to extract bar code charact

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12

Sharma, Anand, and Praneesh Gupta. "Blind Recognition of Parameters of Reed Solomon Code from Intercepted Erroneous Codewords." Defence Science Journal 71, no. 6 (2021): 772–76. http://dx.doi.org/10.14429/dsj.71.15047.

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Error correcting codes are designed for reliable transmission of digital information over a noisy channel. Several papers have been published on blind identification of binary FEC codes but papers reported on the identification of non-binary error correcting codes are less. Due to its strong error correction capability, RS (Reed-Solomon) code is being used widely. So technique for blind recognition of RS code is required to analyse intercepted signal as well as for intelligent communication. This paper presents a technique for extraction of parameters of Reed-Solomon code from intercepted demo

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13

Wang, Xing-Hua, Le Liang, Hong-Wei Sun, Wei-Bin Chen, Can-Can Wang, and Yang-Yang Sun. "Real-Time Identification of Nonstandard Thermal Inkjet Codes on the Surface of Hot-Rolled Steel Sheets in Complex Environments." Advances in Materials Science and Engineering 2022 (July 14, 2022): 1–8. http://dx.doi.org/10.1155/2022/2620316.

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Many steel mills currently rely on thermal spray codes to carry and convey information about the steel plate at different stages of production. Thermal inkjet codes are patterns of numbers, letters, and symbols formed by continuous spraying of high-temperature resistant coatings on the surface of billets, so it is especially important to identify thermal inkjet code information accurately and timely during the processing stage of steel plates. Most of the existing mainstream identification methods rely on manual visual observation and traditional image recognition to obtain them, with low reco

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14

Hennig, Janosch, Fatima Gebauer, and Michael Sattler. "Breaking the protein-RNA recognition code." Cell Cycle 13, no. 23 (2014): 3619–20. http://dx.doi.org/10.4161/15384101.2014.986625.

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15

Suzuki, Masashi, Steven E. Brenner, Mark Gerstein, and Naoto Yagi. "DNA recognition code of transcription factors." "Protein Engineering, Design and Selection" 8, no. 4 (1995): 319–28. http://dx.doi.org/10.1093/protein/8.4.319.

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16

Lee, Daeha, and Soon‐Ja Kim. "Modified chain‐code‐based object recognition." Electronics Letters 51, no. 24 (2015): 1996–97. http://dx.doi.org/10.1049/el.2015.1019.

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17

Nahalka, Jozef. "Protein–RNA recognition: Cracking the code." Journal of Theoretical Biology 343 (February 2014): 9–15. http://dx.doi.org/10.1016/j.jtbi.2013.11.006.

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18

Fellouse, Frederic A., Bing Li, Deanne M. Compaan, Andrew A. Peden, Sarah G. Hymowitz, and Sachdev S. Sidhu. "Molecular Recognition by a Binary Code." Journal of Molecular Biology 348, no. 5 (2005): 1153–62. http://dx.doi.org/10.1016/j.jmb.2005.03.041.

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19

Cho, Hangseo, Jongpil Jeong, Chaegyu Lee, Seokwoo Yun, Kyunga Bang, and Jaebeom Byun. "Design and Implementation for BIC Code Recognition System of Containers using OCR and CRAFT in Smart Logistics." WSEAS TRANSACTIONS ON COMPUTER RESEARCH 11 (June 16, 2023): 62–72. http://dx.doi.org/10.37394/232018.2023.11.6.

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The BIC (Bureau International des Containers et du Transport Intermodal) Code is the identification code for ocean shipping containers and is crucial for logistics, transportation, and security. Accurate recognition of container BIC Code is essential for efficient import and export processes, authorities' ability to intercept illegal goods and safe transportation. Nevertheless, the current practice of employees recognizing and manually entering container BIC codes is inefficient and prone to error. Although automated recognition efforts have been made, challenges remain due to the aging of con

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20

Kessler, Christoph W. "Pattern-Driven Automatic Parallelization." Scientific Programming 5, no. 3 (1996): 251–74. http://dx.doi.org/10.1155/1996/406379.

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This article describes a knowledge-based system for automatic parallelization of a wide class of sequential numerical codes operating on vectors and dense matrices, and for execution on distributed memory message-passing multiprocessors. Its main feature is a fast and powerful pattern recognition tool that locally identifies frequently occurring computations and programming concepts in the source code. This tool also works for dusty deck codes that have been "encrypted" by former machine-specific code transformations. Successful pattern recognition guides sophisticated code transformations inc

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21

Lee, Isack, and Seok Bong Yoo. "Latent-PER: ICA-Latent Code Editing Framework for Portrait Emotion Recognition." Mathematics 10, no. 22 (2022): 4260. http://dx.doi.org/10.3390/math10224260.

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Although real-image emotion recognition has been developed in several studies, an acceptable accuracy level has not been achieved in portrait drawings. This paper proposes a portrait emotion recognition framework based on independent component analysis (ICA) and latent codes to overcome the performance degradation problem in drawings. This framework employs latent code extracted through a generative adversarial network (GAN)-based encoder. It learns independently from factors that interfere with expression recognition, such as color, small occlusion, and various face angles. It is robust again

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22

Ms. J Seetha, Dr. G Manikandan, Ms. S. Hemalatha, and Ms. Vilma Veronica. "QR Code Recognition Based on Image Processing." International Journal of Scientific Research in Science and Technology 11, no. 2 (2024): 160–68. http://dx.doi.org/10.32628/ijsrst52411227.

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To solve the QR code recognition problem caused by ordinary camera collection, the recognition algorithm based on image processing is put forward in this paper. The whole process including image binarization, image tilt correction, image orientation, image geometric correction and image normalization allows images collected on different illumination conditions. Experiments show that the improved method can enhance the recognition speed of two-dimensional code and accuracy. QR i.e. “Quick Response” code is a 2D matrix code that is designed by keeping two points under consideration, i.e. it must

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23

Cheng, Zhi Mei, and Hong Qin Zhu. "Designed and Development of Embedded QR Code Bar Code Recognition System." Advanced Materials Research 482-484 (February 2012): 812–16. http://dx.doi.org/10.4028/www.scientific.net/amr.482-484.812.

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Based on J2ME technology,develop a Embedded QR Code bar code recognition system.This system integrated image graying,image binarization, image rotation and other processing methods to realize bar code pre-process, anti-perspective transformation algorithm is adapted to correct distortion pictures,solved mobile taking picture on problems of image lean, distortion illumination on QR code effectively, have higher identification of image under different lighting conditions.

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24

Wang, Hong Wei, Lin Yang, and Yi Bing Cai. "Blind Recognition for Rate below 1/2 Binary Cyclic Codes." Applied Mechanics and Materials 511-512 (February 2014): 1163–66. http://dx.doi.org/10.4028/www.scientific.net/amm.511-512.1163.

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The blind recognition of channel coding is playing more and more important roles in smart communications. The paper took rate below 1/2 binary cyclic codes to research, we established a model using counter of continuous bits 0. At the basic of studying the features of binary cyclic codes, when the condition about the rate is satisfied, we made a statistics of the continuous bits 0 in a long sequence of code words to get the length of code word n and the length of information k. In the condition of higher BER simulations, we improved the method to make it suitable for estimating the parameter.

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25

Liu, Hengyan, Zhaojun Wu, Limin Zhang, and Wenjun Yan. "Polar Code Parameter Recognition Algorithm Based on Dual Space." Electronics 11, no. 16 (2022): 2511. http://dx.doi.org/10.3390/electronics11162511.

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To improve the performance of polar code parameter recognition in the fields of intelligent communication, communication detection, and network countermeasures, we propose a new recognition scheme for the additive white Gaussian noise (AWGN) channel. The scheme turns parameter recognition problems into hypothetical tests and is effective due to the check relationship between the received codeword and the dual space determined by the correct parameters. First, a sub-matrix is obtained by removing the frozen-bit-index rows of the polar code generator matrix, and then its dual matrix is calculate

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26

Xie, Hui, Feng Hua Wang, and Zhi Tao Huang. "Blind Recognition of Reed-Solomon Codes Based on Histogram Statistic of Galois Field Spectra." Advanced Materials Research 791-793 (September 2013): 2088–91. http://dx.doi.org/10.4028/www.scientific.net/amr.791-793.2088.

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We focus on the recognition of RS code in a reverse-engineering communication system, and an algorithm based on spectral statistic is proposed, which makes use of the spectral characteristics of RS code. When there are some codes with errors in the observations, the spectral histogram statistic is computed, which can improve the probability of detection in the noisy environment. Experimental results are given to illustrate the performances of the method which can get a 90% probability of detection of (255, 223) RS code in the presence of 0.5% code error rate.

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27

FUH, DUU-TONG, and CHING-HSING LUO. "UNSTABLE MORSE CODE RECOGNITION SYSTEM WITH EXPERT-GATING NEURAL NETWORK." Biomedical Engineering: Applications, Basis and Communications 14, no. 01 (2002): 12–19. http://dx.doi.org/10.4015/s1016237202000036.

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The standard Morse code defines the tone ratio (dash/dot) and the silent ratio (dash-space/dotspace) as 3:1. Since human typing ratio can't keep this ratio precisely and the two ratios —tone ratio and silent ratio—are not equal, the Morse code can't be recognized automatically. The requirement of the standard ratio is difficult to satisfy even for an ordinary person. As for the unstable Morse code typing pattern, the auto-recognition algorithms in the literature are not good enough in applications. The disabled persons usually have difficulty in maintaining a stable typing speeds and typing ra

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28

Rida Fethi, Mohamed, Othmane Farhaoui, Imad Zeroual, and Ahmad El Allaoui. "A Progressive Approach to Arabic Character Recognition Using a Modified Freeman Chain Code Algorithm." Data and Metadata 2 (May 8, 2023): 178. http://dx.doi.org/10.56294/dm2023178.

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Arabic character identification presents a significant obstacle to the comprehension and analysis of Arabic text. This paper presents an improved technique that generates Freeman code from handwritten Arabic characters. This code provides the shortest code length without losing character information, accounting for all handwritten Arabic character variants. We tested this code using a set of Arabic characters in various formats to identify Arabic characters in order to take use of the code generated by our enhanced method. We also performed a comparison between our Freeman code and codes gener

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29

Roy, Ramit Kumar, Umapada Pal, Kaushik Roy, and Fumitaka K. Kimura. "A SYSTEM FOR RECOGNITION OF DESTINATION ADDRESS IN POSTAL DOCUMENTS OF INDIA." Malaysian Journal of Computer Science 33, no. 3 (2020): 202–16. http://dx.doi.org/10.22452/mjcs.vol33no3.3.

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Recognition of destination address is compulsory for automation of the postal system in India. Our observation found that such recognition becomes a very challenging task due to inter-mixing of three languages (Hindi, English and the official language of the particular state in which the postal document is supposed to reach).In this paper, our attempt towards development of a dynamic programming based system for city-name and pin code recognition of destination address in postal documents of India not only managed to address the difficulties related to identification of the scripts but also ma

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30

Shekar, B. H., S. S. Bhat, and A. Maysuradze. "RELIABILITY INDEX FOR IRIS CODE MATCHING IN IRIS RECOGNITION SYSTEMS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W12 (May 9, 2019): 197–202. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w12-197-2019.

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<p><strong>Abstract.</strong> Iris code matching is an important stage of iris biometric systems which compares the input iris code with stored patterns of enrolled iris codes and classifies the code into one of classes so that, the claim is accepted or rejected. Several classifier based approaches are proposed by the researchers to improve the recognition accuracy. In this paper, we discuss the factors affecting an iris classifier’s performance and we propose a reliability index for iris matching techniques to quantitatively measure the extent of system reliability, based on

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31

Karrach, Ladislav, and Elena Pivarčiová. "Recognition of Data Matrix Codes in Images and their Applications in Production Processes." Management Systems in Production Engineering 28, no. 3 (2020): 154–61. http://dx.doi.org/10.2478/mspe-2020-0023.

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AbstractData Matrix codes can be a significant factor in increasing productivity and efficiency in production processes. An important point in deploying Data Matrix codes is their recognition and decoding. In this paper is presented a computationally efficient algorithm for locating Data Matrix codes in the images. Image areas that may contain the Data Matrix code are to be identified firstly. To identify these areas, the thresholding, connected components labelling and examining outer bounding-box of the continuous regions is used. Subsequently, to determine the boundaries of the Data Matrix

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32

Wang, Jiafeng, Yang Yue, and Jun Yao. "Statistical Recognition Method of Binary BCH Code." Communications and Network 03, no. 01 (2011): 17–22. http://dx.doi.org/10.4236/cn.2011.31003.

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33

Ebraheem, Sundus, and Reham Al-Atiwi. "Traffic sign recognition by using chain code." AL-Rafidain Journal of Computer Sciences and Mathematics 9, no. 2 (2012): 113–26. http://dx.doi.org/10.33899/csmj.2012.163722.

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34

SUN, Daoda, Jian ZHAO, Rui WANG, Ning FENG, and Jianghua HU. "QR code recognition based on sparse representation." Journal of Computer Applications 33, no. 1 (2013): 179–81. http://dx.doi.org/10.3724/sp.j.1087.2013.00179.

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35

Kulkarni, Vinayak B. "A Colour Code Algorithm For Signature Recognition." ELCVIA Electronic Letters on Computer Vision and Image Analysis 6, no. 1 (2007): 1. http://dx.doi.org/10.5565/rev/elcvia.133.

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36

Zhu, Lianxiang, and Li Li. "Research on blind recognition for RS code." JOURNAL OF ELECTRONIC MEASUREMENT AND INSTRUMENT 27, no. 8 (2014): 781–87. http://dx.doi.org/10.3724/sp.j.1187.2013.00781.

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37

Dumay-Manganti, Marites. "CODE BREAKING APPROACH IN AUTOMATED CHARACTER RECOGNITION." Globus An International Journal of Management & IT 10, no. 2 (2019): 54. http://dx.doi.org/10.46360/globus.220191009.

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38

Lee, Jae-Hwan, Hyun Lee, In-Sik Kang, Sang-Bom Yun, Cheol-Sun Park, and Young-Joon Song. "Recognition of Convolutional Code with Performance Analysis." Journal of Korea Information and Communications Society 37, no. 4A (2012): 260–68. http://dx.doi.org/10.7840/kics.2012.37a.4.260.

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39

Li, Jian, Shuai Guo, and Feng Ye. "Shape Recognition Based on Freeman Chain Code." Advanced Materials Research 317-319 (August 2011): 2490–96. http://dx.doi.org/10.4028/www.scientific.net/amr.317-319.2490.

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In this paper, a shape recognition method based on Freeman chain code has been proposed. According to the detected corners, feature vector of a contour shape can be obtained. And the descriptor of each corner in the feature vector has three components, which are the normalized distance between the corner and the centroid of all the corners, the local main trend of both sides of the corners. By using the feature vector, the matching judgment has been given, and the results of the experiment are shown.

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40

Joseph, E., and T. Pavlidis. "Bar code waveform recognition using peak locations." IEEE Transactions on Pattern Analysis and Machine Intelligence 16, no. 6 (1994): 630–40. http://dx.doi.org/10.1109/34.295907.

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41

LeCun, Y., B. Boser, J. S. Denker, et al. "Backpropagation Applied to Handwritten Zip Code Recognition." Neural Computation 1, no. 4 (1989): 541–51. http://dx.doi.org/10.1162/neco.1989.1.4.541.

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The ability of learning networks to generalize can be greatly enhanced by providing constraints from the task domain. This paper demonstrates how such constraints can be integrated into a backpropagation network through the architecture of the network. This approach has been successfully applied to the recognition of handwritten zip code digits provided by the U.S. Postal Service. A single network learns the entire recognition operation, going from the normalized image of the character to the final classification.

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42

Jeffries, Clark. "Code Recognition with Neural Network Dynamical Systems." SIAM Review 32, no. 4 (1990): 636–51. http://dx.doi.org/10.1137/1032123.

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43

Bertozzi, Carolyn R. "Cracking the carbohydrate code for selectin recognition." Chemistry & Biology 2, no. 11 (1995): 703–8. http://dx.doi.org/10.1016/1074-5521(95)90096-9.

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44

Bublík, Tomáš, and Miroslav Virius. "Scripting Language for Java Source Code Recognition." IERI Procedia 10 (2014): 119–30. http://dx.doi.org/10.1016/j.ieri.2014.09.100.

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45

Kachanov, Vladimir Vladimirovich, Ariana Sergeevna Khitrova, and Sergei Igorevich Markov. "Named Entity Recognition for Code Review Comments." Proceedings of the Institute for System Programming of the RAS 35, no. 5 (2023): 193–214. http://dx.doi.org/10.15514/ispras-2022-35(5)-13.

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This paper addresses the problem of named entities recognition from source code reviews. The paper provides a comparative analysis of existing approaches and proposes its own methods to improve the quality of problem solving. Proposed and implemented improvements include: methods to deal with data imbalances, improved tokenization of input data, the use of large arrays of unlabeled data, and the use of additional binary classifiers. To assess quality, a new set of 3,000 user code reviews was collected and manually labeled. It is shown that the proposed improvements can significantly increase t

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46

AHMED, PERVEZ, and C. Y. SUEN. "COMPUTER RECOGNITION OF TOTALLY UNCONSTRAINED HANDWRITTEN ZIP CODES." International Journal of Pattern Recognition and Artificial Intelligence 01, no. 01 (1987): 1–15. http://dx.doi.org/10.1142/s0218001487000023.

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This paper deals with the application of automatic sorting of envelopes with totally unconstrained handwritten numeric postal ZIP codes and presents a complete model (including preprocessing, feature extraction and classification modules) of a ZIP code reader/sorter. Different recognition methods, including statistical, structural and combined were developed and their performance on real-life ZIP code samples (8540 numerals) were measured. The statistical recognition method was used as a front-end recognizer and predictor of an unknown character. Based on edge classification, a new technique w

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47

Yuan, Shuai, Guo Yun Zhang, Jian Hui Wu, and Long Yuan Guo. "Study of One-Dimensional Bar Code Recognition System." Applied Mechanics and Materials 373-375 (August 2013): 487–90. http://dx.doi.org/10.4028/www.scientific.net/amm.373-375.487.

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Bar code technology has been widely used with the development of computer application, which studies information identification by bar code and conversion from bar code information to computer language for automatic input, identification and statistics. This paper presents system design and realization of recognition system for one-dimensional bar code according with ISBN encoding rule. Encoding rule of common bar code is introduced at first. Bar code image is preprocessed by binaryzation, then the image noise caused by print quality and dirt is filtered by a mean value method. The actual widt

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48

Truc, Nguyen Thanh, and Yong-Tae Kim. "Navigation Method of the Transportation Robot Using Fuzzy Line Tracking and QR Code Recognition." International Journal of Humanoid Robotics 14, no. 02 (2016): 1650027. http://dx.doi.org/10.1142/s0219843616500274.

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In this paper, a navigation method using fuzzy line tracking, QR code recognition and path planning algorithm is proposed for the transportation robot. We build a grid map by attaching QR codes on a floor and using lines that are gaps between tiles. The transportation robot is developed with a camera to capture floor images that is used to detect QR code and extract lines’ parameters by applying linear equation and FIR filter. A fuzzy decision-maker is designed to solve the deviation problem occurring during a navigation process between QR codes. The QR code is used to get the current position

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49

Zhou, Jing, and Zhiping Huang. "Blind Recognition of Binary BCH Codes for Cognitive Radios." Mathematical Problems in Engineering 2016 (2016): 1–6. http://dx.doi.org/10.1155/2016/3013504.

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A novel algorithm of blind recognition of Bose-Chaudhuri-Hocquenghem (BCH) codes is proposed to solve the problem of Adaptive Coding and Modulation (ACM) in cognitive radio systems. The recognition algorithm is based on soft decision situations. The code length is firstly estimated by comparing the Log-Likelihood Ratios (LLRs) of the syndromes, which are obtained according to the minimum binary parity check matrixes of different primitive polynomials. After that, by comparing the LLRs of different minimum polynomials, the code roots and generator polynomial are reconstructed. When comparing wi

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50

Deng, Huaxia, Guoce Hu, Jin Zhang, Mengchao Ma, Xiang Zhong, and Ze Yang. "An Initial Dot Encoding Scheme with Significantly Improved Robustness and Numbers." Applied Sciences 9, no. 22 (2019): 4915. http://dx.doi.org/10.3390/app9224915.

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Abstract:

Coded mark point, as an important part of automatic matching, is widely used in stereo vision and photogrammetry. An encoding scheme named the Initial Dot encoding scheme, has been designed based on the programme of concentric rings, and which is able to solve restrictions on the number of codes and promote the stability of decoding. The designed coding pattern includes three functional points: locating point, start point and coded point. The maximum coding number of the Initial Dot scheme can reach 262,144 when the number of code bits is 18. The recognition experiments show that the Initial D

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