Relevant bibliographies by topics / Subpixel edge detection

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  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'Subpixel edge detection'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Subpixel edge detection"

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Wu, Ji Gang, Kuan Fang He, and Bin Qin. "Subpixel Edge Detection of Autofocus for Micro-Machine Vision System." Advanced Materials Research 216 (March 2011): 228–32. http://dx.doi.org/10.4028/www.scientific.net/amr.216.228.

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Aiming at the subpixle edge detection of speckle in autofocus for micro-machine vision, a novel accurate subpixel edge detection algorithm was proposed. The image of the part to be inspected was binaried by simple threshold algorithm. The noise in image was eliminated by blob area threshold algorithm. The pixel level edge detection was done and the single-pixel width connected pixel level contour was acquired by binary mathematical morphological algorithm. The subpixel level edge detection was completed and the subpixel level contour was obtained by 9×9 pixel rectangular lens algorithm based on cubic spline interpolation. The example result indicate that calculation speed of the algorithm proposed herein is fast, anti-noise performance is high, inspection accuracy is high, and subpixel edge location accuracy can reach to μm level.
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Fabijańska, Anna. "A survey of subpixel edge detection methods for images of heat-emitting metal specimens." International Journal of Applied Mathematics and Computer Science 22, no. 3 (September 1, 2012): 695–710. http://dx.doi.org/10.2478/v10006-012-0052-3.

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Abstract In this paper the problem of accurate edge detection in images of heat-emitting specimens of metals is discussed. The images are provided by the computerized system for high temperature measurements of surface properties of metals and alloys. Subpixel edge detection is applied in the system considered in order to improve the accuracy of surface tension determination. A reconstructive method for subpixel edge detection is introduced. The method uses a Gaussian function in order to reconstruct the gradient function in the neighborhood of a coarse edge and to determine its subpixel position. Results of applying the proposed method in the measurement system considered are presented and compared with those obtained using different methods for subpixel edge detection.
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Shi, Hong Juan, Kai Li Zhang, and Qing Hua Li. "Subpixel Edge Detection for Segmentation of the Pulp Fiber Image." Applied Mechanics and Materials 568-570 (June 2014): 696–700. http://dx.doi.org/10.4028/www.scientific.net/amm.568-570.696.

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In this paper the problem of accurate edge detection for pulp fibers images is discussed. The images are acquired by the smart CCD camera. Subpixel edge detection is considered that applied in the system to improve the measurement accuracy of pulp fibers. The location of a precise edge is the basis of kink index, kink Angle, curl index and other measurement parameters for the pulp fibers. A new method for subpixel edge detection of the pulp fibers is introduced. Canny operator is used to get the pixel level edge. Each edge point determines five pixels in the gradient direction. Then the least squares fitting is used to locate its sub-pixel edge. The measurement results show that the proposed subpixel edge detection method is valid to improve measurement accuracy for real time measuring the pulp fiber parameters.
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Zhang, Xi, Zixie Guo, Xiangwei Liu, and Longjia Zhang. "Research on Subpixel Algorithm of Fixed-Point Tool Path Measurement." Computational Intelligence and Neuroscience 2021 (September 3, 2021): 1–9. http://dx.doi.org/10.1155/2021/7270908.

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Tool safety is an important part of machining and machine tool safety, and machine tool path image detection can effectively obtain the in-machine condition of a tool. To obtain an accurate image edge and improve image processing accuracy, a novel subpixel edge detection method is proposed in this study. The precontour is segmented by binarization, the second derivative in the neighborhood of the demand point is calculated, and the obtained value is sampled according to the specified rules for curve fitting. The point whose curve ordinate is 0 is the subpixel position. The experiment proves that an improved subpixel edge can be obtained. Results show that the proposed method can extract a satisfactory subpixel contour, which is more accurate and reliable than the edge results obtained by several current pixel-level operators, such as the Canny operator, and can be used in edge detection with high-accuracy requirements, such as the contour detection of online tools.
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Duan, Zhenyun, Ning Wang, Jingshun Fu, Wenhui Zhao, Boqiang Duan, and Jungui Zhao. "High Precision Edge Detection Algorithm for Mechanical Parts." Measurement Science Review 18, no. 2 (April 1, 2018): 65–71. http://dx.doi.org/10.1515/msr-2018-0010.

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AbstractHigh precision and high efficiency measurement is becoming an imperative requirement for a lot of mechanical parts. So in this study, a subpixel-level edge detection algorithm based on the Gaussian integral model is proposed. For this purpose, the step edge normal section line Gaussian integral model of the backlight image is constructed, combined with the point spread function and the single step model. Then gray value of discrete points on the normal section line of pixel edge is calculated by surface interpolation, and the coordinate as well as gray information affected by noise is fitted in accordance with the Gaussian integral model. Therefore, a precise location of a subpixel edge was determined by searching the mean point. Finally, a gear tooth was measured by M&M3525 gear measurement center to verify the proposed algorithm. The theoretical analysis and experimental results show that the local edge fluctuation is reduced effectively by the proposed method in comparison with the existing subpixel edge detection algorithms. The subpixel edge location accuracy and computation speed are improved. And the maximum error of gear tooth profile total deviation is 1.9 μm compared with measurement result with gear measurement center. It indicates that the method has high reliability to meet the requirement of high precision measurement.
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Yang, Hao, and Lei Pei. "Subpixel Edge Detection Algorithm of the Glass Bottle Based on Zernike Moments." Applied Mechanics and Materials 80-81 (July 2011): 1345–49. http://dx.doi.org/10.4028/www.scientific.net/amm.80-81.1345.

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The accuracy of edge detection determines the accuracy of actual dimension measurement，in order to improve the measuring accuracy, this paper proposes a fast algorithm of detecting the glass bottle dimension based on Zernike moments. Firstly, combines the traditional Zernike moment-based method with Otsu adaptive threshold algorithm and a new fast algorithm for edge detection is proposed. Then uses this fast algorithm to detect the edge of glass bottle with subpixel-level and uses the least square method to fit ellipses formed by the glass bottle mouth and bottom. Calibrated the system with standard gauge block and obtain the actual dimension at last. Experimental results show that the improved algorithm not only can make the edge detection reach the subpixel-level accuracy, but also can avoid the edge misidentification and inefficient causing by repeatedly manual adjustments to select the threshold value when detecting the edge. Making a rapid, accurate, non-contact measuring system becomes a reality.
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Ghosal, Sugata, and Rajiv Mehrotra. "Orthogonal moment operators for subpixel edge detection." Pattern Recognition 26, no. 2 (February 1993): 295–306. http://dx.doi.org/10.1016/0031-3203(93)90038-x.

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Luo, Xin, Li Ming Wu, and De Zhi Zeng. "Application Research on Precision Detection of Small Gear with Composite Edge Detection Method." Applied Mechanics and Materials 333-335 (July 2013): 1123–28. http://dx.doi.org/10.4028/www.scientific.net/amm.333-335.1123.

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Vision-based measurement method can be widely used for a variety of real-time and online precision measurements, and particularly well suited for dynamic real-time precision measurement of geometry parameters of the part, which has advantages of non-contact, high-speed, big dynamic range, rich amount of information, and relatively low cost. After the study of vision-based online detection system of small gear, we propose a composite subpixel edge detection method, which combines the four-way weighted differential algorithm based on the classic Sobel operator and OFMM (Orthogonal Fourier-Mellin Moment), aiming at achieving the precision location of the subpixel edge firstly. And then detect tooth profile defects rapidly through scanning circularly the edge image, according to the structural characteristics of gears. The theoretical analysis and experimental results show that the detection method has so high accuracy and speed that it can meet the industrial online tests requirements.
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Luo, Yuan, Chao Ji, Yi Zhang, and Zhang Fang Hu. "A Fractal Based Subpixel Image Edge Detection Algorithm." Applied Mechanics and Materials 239-240 (December 2012): 1546–51. http://dx.doi.org/10.4028/www.scientific.net/amm.239-240.1546.

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Application of machine vision method for MEMS dynamic parameters were measured, the testing image have a certain degree of ambiguity.This paper presents a sub-pixel algorithm based on fractal and wavelet transform: Firstly, using self-similar characteristics of fractal interpolation to overcome the problem ,that can not be accurate interpolation and the edge of the image reconstruction. Then because of abilities of high resolution and anti-noise,using wavelet transform modulus maxima,the image edge detection.The experimental results show that the algorithm can reach 0.02 pixel accuracy.
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Overington, Ian, and Philip Greenway. "Practical first-difference edge detection with subpixel accuracy." Image and Vision Computing 5, no. 3 (August 1987): 217–24. http://dx.doi.org/10.1016/0262-8856(87)90052-7.

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Dissertations / Theses on the topic "Subpixel edge detection"

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De, Rosa Andrea. "Metodo di Edge-Detection basato sul calcolo di aree parziali." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2018. http://amslaurea.unibo.it/15805/.

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In questo lavoro, viene proposto un metodo di Edge-Detection, in immagini rumorose e con sfuocamento. Il problema è stato posto da Marposs, che fornisce sistemi di misura di alta precisione, quindi è stato necessario applicare un metodo di detezione di edges a livello subpixel. È stato utilizzato il funzionale di Perona Malik per il metodo di denoising e un metodo basato sul calcolo di aree parziali per il subpixed edge detection. Il metodo raggiunge dei buoni risultati anche in situazioni di alto di rumore e sfocamento. Verranno mostrati risultati sia riguardo all'accuratezza dell'edge-detection di contorni rettilinei, con varie inclinazioni, che riguardo la ripetibilità. Infine verranno accennati alcuni risultati nel caso di edge curvilinei e possibili sviluppi futuri per migliorarne le prestazioni.
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Tabbone, Salvatore-Antoine. "Détection multi-échelle de contours subpixel et de jonctions." Vandoeuvre-les-Nancy, INPL, 1994. http://www.theses.fr/1994INPL021N.

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Un système de vision se décompose généralement en plusieurs niveaux. Le premier niveau (bas niveau) a pour objectif d'extraire, de l'énorme quantité d'information contenue dans une image, des primitives robustes et exploitables. La qualité des résultats des niveaux supérieurs est donc tributaire de celle du bas niveau. Nous tentons de répondre aux attentes des niveaux supérieurs d'un système de vision en leur fournissant des informations robustes, exploitables et aussi proches que possible de la scène observée. Nous proposons un système complet de traitement bas niveau d'images à niveau de gris. Une image est décrite à plusieurs échelles (détection multi-échelle) en termes de jonctions et de contours avec une précision subpixel. Un algorithme de fermeture de contours fait coopérer les contours et les jonctions détectés. Notre système est fonde sur des études originales de comportement de modèles d'indices vis-à-vis d'un détecteur de contours
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Čírtek, Jiří. "Sledování malých změn objektů." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2008. http://www.nusl.cz/ntk/nusl-217199.

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This diploma thesis inspects problems with specification location of edges with higher accuracy then one pixel (subpixel accuracy). In terms of this assignment has been created program, which generates three different shapes of objects. With change of parameters in program is measuring location of gravitational center on objects with subpixel accuracy. Obtained data of gravitational center deviations are depictured in graphs.
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Kohoutek, Michal. "Metoda fyzikálního modelování přechodových hran v obraze pro určení skutečné pozice obrysu předmětu." Doctoral thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2009. http://www.nusl.cz/ntk/nusl-233452.

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Doctoral thesis is focused on a design of a new original image transition edge physical modeling method for exact object shape position determination. Automatic Optical Inspection systems for the high accuracy optical measurements is main application area for designed method. The new method design is based on precise physical analysis of a defined imaging system. Object side telecentric lens, telecentric backlight source and CCD video camera are main parts of the analyzed imaging system. New image transition edge physical model and method for accurate shape position detection within the model are derived by geometrical and Fourier optics imaging system analysis. Possible influences of the model parameters changes to the accuracy of shape position detection are studied precisely. A new modeling function suitable for implementation in a new optimal approximation method is derived from the physical transition edge model. The modeling function optimal approximation method is implemented in to a Tester2D measuring system and verified by length etalon measurements. The Tester2D measuring system was successfully accredited for dimensions measurement in range with accuracy up to . Documentation of results of the accreditation process with the record of obtained results from measurement system in scope of preformed interlaboratory comparison tests are appended to the doctoral thesis.
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Shu, Chin-Hao, and 徐俊豪. "Development of A New Robust Subpixel Edge Detection Technique." Thesis, 2000. http://ndltd.ncl.edu.tw/handle/45496426819860108189.

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碩士
國立中興大學
機械工程學系
88
Subpixel edge detection method in machine vision mainly includes edge model and edge estimation method. Most of the conventional one-dimensional edge estimation methods use the ideal step or the two-sided exponential function as edge model and the center of shape method or the least-square method as edge estimation tool. Subpixel edges are estimated by one of the four cross combination approaches. When the images obtained are blurred or out of focus, the performances of these methods degrade tremendously. In this thesis, the bipolar continuous function and the correlation method are adopted as new edge model and subpixel edge estimation approach, respectively. Performances comparisons among the four possible subpixel edge estimation methods are carried out by real experiments to improve the accuracy and robustness. To further reduce the computing time of the one-dimensional methods, two new two-dimensional subpixel edge estimation methods are proposed in this study. In these two new approaches, the two-dimensional two-sided exponential function is chosen as the edge model. The two-dimensional least-square method and the correlation method are the estimation tools, respectively. Experimental results show that all the 1-D and 2-D estimation methods proposed outmatch the conventional methods both in system stability and computing time.
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Cheng, Wen-Wei, and 鄭文瑋. "An Edge Detector with Subpixel Accuracy and Its Applications." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/nh334m.

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碩士
銘傳大學
資訊傳播工程學系碩士班
93
There are sharps and blur case after enlarge images, it is the most important problem of traditional image enlargement technology. Therefore, it will decrease the resolution and accuracy of images. Because of the above-mentioned, we propose an edge detection algorithm with subpixel accuracy. The method includes two steps: 1.image is processed by Sobel edge detection method first that extracts probable edge points. Next, a subpixel accuracy edge detector is used to estimate the edge equation and gray values both sides of the edge automatically, and use them to enlarge the image. The main advantages are that edges can keep distinct when image was enlarged and edge points recovered from noise images. In this thesis, our points are finding the real image edges that before Gaussian blur effect, estimated the both side original gray value of edges, and it can be obtain the line equation of edges in real number, to enhance the accuracy of line equation, that could keep edges intact after image enlargement.
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Book chapters on the topic "Subpixel edge detection"

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Trujillo-Pino, A., K. Krissian, D. Santana-Cedrés, J. Esclarín-Monreal, and J. M. Carreira-Villamor. "A Subpixel Edge Detector Applied to Aortic Dissection Detection." In Computer Aided Systems Theory – EUROCAST 2011, 217–24. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-27579-1_28.

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Zhang, Huan, Cai Meng, and Zhaoxi Li. "Rock-Ring Accuracy Improvement in Infrared Satellite Image with Subpixel Edge Detection." In Image and Graphics Technologies and Applications, 180–91. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-1702-6_18.

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Ghosal, Sugata, and Rajiv Mehrotra. "Subpixel Edge Detection." In Computer Vision: Systems, Theory and Applications, 99–115. WORLD SCIENTIFIC, 1993. http://dx.doi.org/10.1142/9789814343312_0007.

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Bilynsky, Y. Y., P. M. Ratushny, A. Kotyra, P. Kisala, M. Junisbekov, and E. Amirgalijev. "Subpixel edge detection and localisation based on low-frequency filtering." In Information Technology in Medical Diagnostics, 95–106. CRC Press, 2017. http://dx.doi.org/10.1201/9781315098050-5.

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Qiu, Yuanhong, and Bin Li. "A subpixel edge detection algorithm for the vision-based localisation of Light Emitting Diode (LED) chips." In Automotive, Mechanical and Electrical Engineering, 339–43. CRC Press, 2017. http://dx.doi.org/10.1201/9781315210445-62.

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Conference papers on the topic "Subpixel edge detection"

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Manmatha, R. "Edge Detection To Subpixel Accuracy." In Applications of Artificial Intelligence V, edited by John F. Gilmore. SPIE, 1987. http://dx.doi.org/10.1117/12.940627.

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Koplowitz, Jack, and Xiaobing Lee. "Edge detection with subpixel accuracy." In Orlando '91, Orlando, FL, edited by Firooz A. Sadjadi. SPIE, 1991. http://dx.doi.org/10.1117/12.44901.

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Su, Chung-Yen, Li-An Yu, and Nai-Kuei Chen. "Effective subpixel edge detection for LED probes." In 2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC). IEEE, 2016. http://dx.doi.org/10.1109/smc.2016.7844270.

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Jivin, Ilya, and Stanley R. Rotman. "Edge impact on subpixel target detection in hyperspectral imagery." In 2008 IEEE 25th Convention of Electrical and Electronics Engineers in Israel (IEEEI). IEEE, 2008. http://dx.doi.org/10.1109/eeei.2008.4736666.

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Xiang, Fengtao, Zhengzhi Wang, and Xingsheng Yuan. "Subpixel Edge Detection: An Improved Zernike Orthogonal Moments Method." In 2013 5th International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC). IEEE, 2013. http://dx.doi.org/10.1109/ihmsc.2013.11.

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Mentin, Christian, Eugen Brenner, and Robin H. Priewald. "Subpixel resolution edge detection techniques for linear sensor arrays." In 2016 International Conference on Broadband Communications for Next Generation Networks and Multimedia Applications (CoBCom). IEEE, 2016. http://dx.doi.org/10.1109/cobcom.2016.7593498.

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Bylinsky, Yosip Y., Andrzej Kotyra, Konrad Gromaszek, and Aigul Iskakova. "Subpixel edge detection method based on low-frequency filtering." In Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2016, edited by Ryszard S. Romaniuk. SPIE, 2016. http://dx.doi.org/10.1117/12.2249336.

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Zhang, Kun, Haiqing Chen, Qingwen Liang, Chong Huang, and Jiakun Xu. "Subpixel edge-detection algorithm based on pseudo-Zernike moments." In 5th International Symposium on Advanced Optical Manufacturing and Testing Technologies, edited by Ya-Dong Jiang, Bernard Kippelen, and Junsheng Yu. SPIE, 2010. http://dx.doi.org/10.1117/12.866023.

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Truchetet, Frederic, and Olivier Laligant. "Subpixel edge detection for dimensional control by artificial vision." In Electronic Imaging, edited by Kenneth W. Tobin, Jr. SPIE, 2000. http://dx.doi.org/10.1117/12.380066.

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Venkatachalam, Vidya, and Richard M. Wasserman. "Comprehensive investigation of subpixel edge detection schemes in metrology." In Electronic Imaging 2003, edited by Martin A. Hunt and Jeffery R. Price. SPIE, 2003. http://dx.doi.org/10.1117/12.474070.

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