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Journal articles on the topic 'Subpixel edge detection'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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1

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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2

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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3

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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4

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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5

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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6

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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7

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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8

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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9

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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10

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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11

Sun, Qiucheng, Yueqian Hou, and Qingchang Tan. "A subpixel edge detection method based on an arctangent edge model." Optik 127, no. 14 (July 2016): 5702–10. http://dx.doi.org/10.1016/j.ijleo.2016.03.058.

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12

Truchetet, F. "Subpixel edge detection for dimensional control by artificial vision." Journal of Electronic Imaging 10, no. 1 (January 1, 2001): 234. http://dx.doi.org/10.1117/1.1316089.

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13

Wang, Le, Li Zou, and Shengmei Zhao. "Edge detection based on subpixel-speckle-shifting ghost imaging." Optics Communications 407 (January 2018): 181–85. http://dx.doi.org/10.1016/j.optcom.2017.09.002.

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14

Bai, Xin, Mijia Yang, and Beena Ajmera. "An Advanced Edge-Detection Method for Noncontact Structural Displacement Monitoring." Sensors 20, no. 17 (September 1, 2020): 4941. http://dx.doi.org/10.3390/s20174941.

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A non-contact vision sensor system for monitoring structural displacements with advanced Zernike subpixel edge detection technique is suggested in this paper. Edge detection can detect features of objects effectively without using templates. Subpixel techniques provide more accurate and cost-effective results when compared to integer pixel methods. Built on these two techniques, a new version sensor method was developed to detect the vibrations of structures in this study. Satisfactory agreements were found between the displacements measured by the vision sensor system and those recorded by the Multipurpose Testing System (MTS). A field test was then carried out on a street sign using the proposed vision system. Satisfactory results were obtained using the new version of the sensor system at many points simultaneously without any manually marked targets. Moreover, the system was able to provide natural frequencies and mode shapes of the target instantaneously, which could be used to accurately locate damage.

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15

Sun, Tiebo, and Hong Li. "On High-precision Subpixel-based Drilling Technique for Suture Needles with Thread." Open Mechanical Engineering Journal 8, no. 1 (December 31, 2014): 607–12. http://dx.doi.org/10.2174/1874155x01408010607.

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In order to improve the automation of end-hole drilling process in the production of suture needles with thread, a high-precision subpixel-based drilling method is proposed. According to the edge detection principle in mathematical morphology, combined with the characteristics of the magnified images of the ends of suture needles to be drilled, the morphological edge detection operators with variable structural elements are constructed to achieve noise suppression and fully extract the detailed information of edges of images of needle end holes to be drilled. Then, the subdivision method of spatial moments is adopted to realize the subpixel positioning of pixel-level edges. Finally, least squares fitting method is used to achieve the high-precision positioning of center of needle end hole to be drilled. The experimental results of the 0.5 mm needle samples show that the drilling method proposed in this study has a concentricity error no more than ± 0.2 μm and an average drilling time of 0.65S. Moreover, the method also boasts good real-time performance and stability and meets the automated production needs of drilling process of suture needles with thread.

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16

Zhang, Baojian, Linfeng Bai, and Xiangjin Zeng. "A Novel Subpixel Edge Detection Based on the Zernike Moment." Information Technology Journal 9, no. 1 (December 15, 2009): 41–47. http://dx.doi.org/10.3923/itj.2010.41.47.

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17

Ying-Dong, Qu, Cui Cheng-Song, Chen San-Ben, and Li Jin-Quan. "A fast subpixel edge detection method using Sobel–Zernike moments operator." Image and Vision Computing 23, no. 1 (January 2005): 11–17. http://dx.doi.org/10.1016/j.imavis.2004.07.003.

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18

Javed, Aisha, Hyeongill Lee, Byeongil Kim, and Youkyung Han. "Vibration measurement of a rotating cylindrical structure using subpixel-based edge detection and edge tracking." Mechanical Systems and Signal Processing 166 (March 2022): 108437. http://dx.doi.org/10.1016/j.ymssp.2021.108437.

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19

Li, Y. S., T. Y. Young, and J. A. Magerl. "Subpixel edge detection and estimation with a microprocessor-controlled line scan camera." IEEE Transactions on Industrial Electronics 35, no. 1 (1988): 105–12. http://dx.doi.org/10.1109/41.3072.

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20

Chiou, Yih‐Chih, and Yu‐Teng Liang. "An effective corner detection method using subpixel edge detector and Gaussian filter." Sensor Review 30, no. 1 (January 26, 2010): 51–61. http://dx.doi.org/10.1108/02602281011010790.

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21

Hermosilla, T., E. Bermejo, A. Balaguer, and L. A. Ruiz. "Non-linear fourth-order image interpolation for subpixel edge detection and localization." Image and Vision Computing 26, no. 9 (September 2008): 1240–48. http://dx.doi.org/10.1016/j.imavis.2008.02.012.

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22

Wu, Ji Gang, Xue Jun Li, and Bin Qin. "Research on Dimensional Inspection System of Thin Sheet Part Based on Machine Vision." Advanced Engineering Forum 2-3 (December 2011): 469–74. http://dx.doi.org/10.4028/www.scientific.net/aef.2-3.469.

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Key technologies of dimensional inspection system of thin sheet part based on machine vision are investigated, and an entire machine vision inspection system is developed. A cad information-based line scanning step adaptive optimization method used for image grabbing of inspected part is proposed. A rectangle lens subpixel edge detection method based on cubic spline interpolation used for edge detection is advanced. A planar contour primitive recognition method based on curvature and HOUGH transform used for image recognition is raised. The inspection accuracy of the inspection system can reach to 1μm, and the inspection time can satisfy the requirements of on-line real-time inspection, so the inspection system is feasible.

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23

GAO, Shi-Yi. "Improved Algorithm about Subpixel Edge Detection of Image Based on Zernike Orthogonal Moments." Acta Automatica Sinica 34, no. 9 (March 17, 2009): 1163–68. http://dx.doi.org/10.3724/sp.j.1004.2008.01163.

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24

Cheng, Shyi-Chyi, and Tian-Luu Wu. "Subpixel edge detection of color images by principal axis analysis and moment-preserving principle." Pattern Recognition 38, no. 4 (April 2005): 527–37. http://dx.doi.org/10.1016/j.patcog.2004.08.016.

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25

Duke, Daniel, Damon Honnery, and Julio Soria. "A Comparison of Subpixel Edge Detection and Correlation Algorithms for the Measurement of Sprays." International Journal of Spray and Combustion Dynamics 3, no. 2 (June 2011): 93–109. http://dx.doi.org/10.1260/1756-8277.3.2.93.

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26

Wang, Jang Ping, Guo Ming Huang, and Sheng Hua Yurs. "Profiles Detection in Ring Convex Forming by ACLN with Sub-Pixel Accuracy." Key Engineering Materials 364-366 (December 2007): 199–204. http://dx.doi.org/10.4028/www.scientific.net/kem.364-366.199.

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An optical measuring system for the ring test is proposed. In this approach, the machine vision inspection equipment is first built to record and capture the images of ring test from the digital camcorder.The image processing procedures to detect and locate the edge points of the inner and outer radii in ring convex forming are presented. Unlike the conventional sub-pixel estimation based on gray-level values, the quantity (8 bits) of color’s scale has been adopted. In image processing procedures, a clustering method called Adaptive Competitive Learning Network (ACLN) is first used to classify the image hues which represent the different heights of bulge profiles on the top of ring, and then the edge points can be searched by the interpolation step of subpixel accuracy. The calibration curves constructed by the mode of non-constant friction factor called F-value approach is designed to compare and check with the measurement data. The experimental results will be presented and discussed in this study.

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27

Cui, Ji Wen, and Jiu Bin Tan. "A Circle Contour Measurement Technique Based on Randomized Hough Transform Using Gradient Information." Key Engineering Materials 295-296 (October 2005): 277–82. http://dx.doi.org/10.4028/www.scientific.net/kem.295-296.277.

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Hough Transform (HT) is an image edge detection technique which is widely used in pattern recognition and computer vision. In this paper the fundamental principle of HT is analyzed and the defect of HT and Randomized Hough Transform (RHT) is indicated. An algorithm based on RHT and the information of grayscale and gradient in image is proposed. It uses the property of the pattern and is mainly used for detection of circle and arc contour measurement. This algorithm can decrease memory usage in computer by a multi to one mapping, accelerate the calculation speed by parallel algorithm, improve the edge detection accuracy by subpixel division, obtain the parameters of object by applying least square fitting algorithm. Based on the principle, a measurement system with high accuracy and efficiency in image capturing and processing is developed. Experiments are carried out in the system. The result of experiment has certified the feasibility and validity of the algorithm.

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28

Mizotin, M. M. "Subpixel Edge Detection in the Problem of Determining the Surface Tension from an Axisymmetric Drop Profile." Computational Mathematics and Modeling 25, no. 3 (June 18, 2014): 365–80. http://dx.doi.org/10.1007/s10598-014-9233-2.

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29

Liu, Jiang Sheng, and Juan Qian. "Research on Measuring Accuracy Improvement for Tool Presetter." Key Engineering Materials 572 (September 2013): 261–64. http://dx.doi.org/10.4028/www.scientific.net/kem.572.261.

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Tool presetter is a type of precision measuring instrument that associates to CNC machine tools and machining centers, which integrates the technologies of optics, mechanics and electrics all together, and its measuring accuracy gives direct influence on machining accuracy of CNC machines. The main factors that influence measuring accuracy of tool presetter include: image edge detection, image positioning and accuracy of its mechanical system. This paper gives analysis on these main factors and puts forward three newly developed algorithms for improving measuring accuracy of tool presetter. First algorithm is image edge detection algorithm based on subpixel that increases the edge positioning accuracy by more than 10 times. Second one is uniformity compensation algorithm for whole view measurement that is able to capture accurate real pixel size so that image movement is more precise, which further increases the measuring accuracy. The third one is linear compensation algorithm in the measuring space that makes effective compensation to the mechanical system errors, which can compensate any position in measurement space so that system accuracy increases significantly. These algorithms are tested in CoVis software and the results show that the total measuring accuracy of tool presetter is improved dramtically to 2 μm.

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30

Baba, M., and K. Ohtani. "A novel subpixel edge detection system for dimension measurement and object localization using an analogue-based approach." Journal of Optics A: Pure and Applied Optics 3, no. 4 (June 25, 2001): 276–83. http://dx.doi.org/10.1088/1464-4258/3/4/308.

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31

Yuan, Jiehong, Peng Dai, Dong Liang, Shiming Zhou, Shijie Xiao, and Xiuqiang Liang. "Grid Deformation Real-Time Measurement System of Ion Thruster Based on Videometrics." Applied Sciences 9, no. 9 (April 28, 2019): 1759. http://dx.doi.org/10.3390/app9091759.

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In order to conduct high-precision measurement of the LIPS-300 ion thruster grid deformation in a vacuum, high-temperature, and plasma environment, a noncontact videometrics system using a telemicroscope was designed. Based on the captured image, the interactive partitioning edge detection method (IPEDM) was used to obtain stable and clear edges of multiple circular cooperative targets. Meanwhile, magnification factor calibration, rotation angle correction, and subpixel-level grid deformation measurement were performed with cooperative targets. The measurement results show that under the power of 750 W in the discharge chamber, the maximum thermal deformation of the screen grid is 1120 μm, and the gap between the screen grid and the accelerator grid is reduced by 420 μm. An accuracy assessment of the system shows that the grid deformation measurement accuracy is better than 12 μm, and the system satisfies the requirement of high-precision real-time measurements of the grid thermal deformation of the ion thruster under the discharge-chamber-running condition and the plasma-beam-extraction condition.

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32

Schellhorn, M., M. Rosenberger, M. Correns, M. Blau, A. Göpfert, M. Rückwardt, and G. Linss. "Field programmable gate array based hardware implementation of a gradient filter for edge detection in colour images with subpixel precision." Journal of Physics: Conference Series 238 (July 1, 2010): 012029. http://dx.doi.org/10.1088/1742-6596/238/1/012029.

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33

Jiang, Xiuqiang, Shuang Li, Long Gu, Jun Sun, and Dongdong Xiao. "Optical Image Generation and High-precision Line-of-Sight Extraction for Mars Approach Navigation." Journal of Navigation 72, no. 1 (July 3, 2018): 229–52. http://dx.doi.org/10.1017/s0373463318000450.

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A high-precision line-of-sight extraction technique is essential for autonomous optical navigation during the Mars approach phase. To support future Mars exploration missions, an optical image simulation system is a necessary ground verification facility for Mars image generation and line-of-sight extraction algorithm tests. In this paper, an optical image generation procedure is first developed according to projection relationships, reference flight profiles and camera parameters. Next, a hybrid image processing and subpixel-level line-of-sight extraction algorithm is proposed through modification of moment-based sub-pixel edge detection and improvement of direct least-square fitting approaches. Finally, an optical image simulation system is established, and the experimental results show that the proposed procedure can effectively simulate the optical image in the field-of-view of a Mars spacecraft, and the hybrid extraction algorithm can obtain high-precision Mars centroid information.

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34

Wang, Pengpeng, Xiaoxia Guo, Yong Sang, Longtan Shao, Zenan Yin, and Yudi Wang. "Measurement of local and volumetric deformation in geotechnical triaxial testing using 3D-digital image correlation and a subpixel edge detection algorithm." Acta Geotechnica 15, no. 10 (May 25, 2020): 2891–904. http://dx.doi.org/10.1007/s11440-020-00975-z.

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35

Lin, Paul P., Qing Guo, and Xiaolong Li. "Online Inspection for Glass Fiber Forming." Journal of Manufacturing Science and Engineering 129, no. 1 (August 31, 2006): 164–71. http://dx.doi.org/10.1115/1.2375138.

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Glass fiber forming is a complicated process in which many factors could affect the quality of fibers. The forming machine has many fiber-forming tubes that are close to each other and arranged in several layers. The closeness results in inadequate lighting and unwanted video signals. An anti-causal zero-phase filter was employed to remove noise with insignificant pixel location shift or distortion. In addition to the noise, the unwanted video signals constantly moving from one place to another also presented a challenge in image analysis. These signals were identified by a trained neural network that classified patterns. The unwanted signal identification through instant pattern classification made online inspection possible. During the fiber drawing process, the diameters of glass forming tubes and the profiles of glass melting cones were closely monitored and measured online in order to control the final fiber diameter. The accurate diameter measurements were accomplished by the noise removal along with a subpixel-resolution based edge detection technique. The results thus obtained for noise removal and unwanted video signals identification were quite good. The fiber diameter measurements were performed online, and the entire inspection process was automated with the aid of a programmable logic controller.

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36

Borcovas, Evaldas, and Gintautas Daunys. "TRACKING OF HEAD POSITION RELATIVE TO THE SCREEN USING HEAD MOUNTED CAMERA / GALVOS POZICIJOS NUSTATYMAS EKRANO ATŽVILGIU NAUDOJANT ANT GALVOS PRITVIRTINTĄ KAMERĄ." Mokslas - Lietuvos ateitis 5, no. 2 (May 24, 2013): 65–69. http://dx.doi.org/10.3846/mla.2013.10.

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In this paper head position locating systems were analyzed. There were reviewed scientific articles with different proposed methods. The chosen system is with the camera located on the user head. The main parameters of the head positioning systems were analyzed. The procedure laid down in what order parameters are found. The diagram of the system and detail block diagram of the algorithm were provided. Realization of the algorithm used: edge detection method (Sobel), the adjustment algorithm (Subpixel). System is realized in Matlab and C# environment. Determine the optimal parameters for the algorithm execution. Execution of the algorithm in Matlab environment is 1.2 s and C # environment – 126 ms. During the examination of the longest executing algorithm segment, it was found that image filtering is carried out in 107 ms. It is noted that the uncertainty of the algorithm can be divided into static and measurement. The maximum static uncertainty while measuring head position parameters is 1.63 mm and orientation parameters – 0.16°. The maximum measurement uncertainty while measuring head position parameters is 4 mm and orientation parameters – 0.11°. Santrauka Nagrinėjamos galvos padėties pozicionavimo sistemos. Apžvelgti moksliniai straipsniai, kuriuose pateikiami įvairūs siūlomi metodai. Pasirinkta sistema, kai kamera pritvirtinama vartotojui ant galvos. Išskirti pagrindiniai galvos padėties nustatymo parametrai, nustatytas parametrų suradimo eiliškumas, pateikta sistemos schema ir detali algoritmo blokinė schema. Algoritmui įgyvendinti taikyti briaunų radimo (Sobel) ir algoritmo tikslinimo (Subpixel) metodai. Sistema įgyvendinta Matlab ir C# aplinkose. Nustatyti optimalūs algoritmo vykdymo parametrai. Naudojamo kompiuterio procesorius Intel Pentium dual core T4500 – 2,3 GHz. Vidutinis algoritmo veikimo laikas Matlab aplinkoje yra 1,2 s, o C# aplinkoje – 126 ms. Ištyrus algoritmo segmentų vykdymo laiką, pastebėta, kad ilgiausiai vykdomas vaizdo filtravimas – 107 ms. Parodyta, kad algoritmo neapibrėžtis galima suskirstyti į statines ir matavimo neapibrėžtis. Maksimali statinė neapibrėžtis, matuojant galvos pozicijos padėtį, yra 1,63 mm, matuojant orientacijos parametrus – 0,16°. Maksimali matavimo neapibrėžtis yra 4,0 mm, matuojant galvos padėties parametrus, ir 0,11° – orientacijos parametrus.

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37

Zhan, Yinhu, Shaojie Chen, and Donghan He. "High-Precision Heading Determination Based on the Sun for Mars Rover." Advances in Astronomy 2018 (August 1, 2018): 1–14. http://dx.doi.org/10.1155/2018/1493954.

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Since the American Mars Exploration Rover Opportunity landed on Mars in 2004, it has travelled more than 40 km, and heading-determination technology based on its sun sensor has played an important role in safe driving of the rover. A high-precision heading-determination method will always play a significant role in the rover’s autonomous navigation system, and the precision of the measured heading strongly affects the navigation results. In order to improve the heading precision to the 1-arcminute level, this paper puts forward a novel calibration algorithm for solving the comparable distortion of large-field sun sensor by introducing an antisymmetric matrix. The sun sensor and inclinometer alignment model are then described in detail to maintain a high-precision horizon datum, and a strict sun image centroid-extraction algorithm combining subpixel edge detection with circle or ellipse fitting is presented. A prototype comprising a sun sensor, electronic inclinometer, and chip-scale atomic clock is developed for testing the algorithms, models, and methods presented in this paper. Three field tests were conducted in different months during 2017. The results show that the precision of the heading determination reaches 0.28–0.97′ (1σ) and the centroid error of the sun image and the sun elevation are major factors that affect the heading precision.

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38

Kisworo, M. "Detection of curved edges at subpixel accuracy using deformable models." IEE Proceedings - Vision, Image, and Signal Processing 142, no. 5 (1995): 304. http://dx.doi.org/10.1049/ip-vis:19952175.

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Zhang, Jun, Tingjin Luo, Gui Gao, and Lin Lian. "Junction Point Detection Algorithm for SAR Image." International Journal of Antennas and Propagation 2013 (2013): 1–9. http://dx.doi.org/10.1155/2013/357379.

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In this paper, we propose a novel junction point detector based on an azimuth consensus for remote sensing images. To eliminate the impact of noise and some noncorrelated edges of SAR image, an azimuth consensus constraint is developed. In addition to detecting the locations of junctions at the subpixel level, this operator recognizes their structures as well. A new formula that includes a minimization criterion for the total weighted distance is proposed to compute the locations of junction points accurately. Compared with other well-known detectors, including Forstner, JUDOCA, and CPDA, the experimental results indicate that our operator outperforms them both in location accuracy of junction points and in angle accuracy of branch edges. Moreover, our method possesses satisfying robustness to the impact of noise and changes of the SAR images. Our operator can be potentially used to solve a number of problems in computer vision, such as SAR image registration, wide-baseline matching, and UAV navigation system.

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Frommholz, D., M. Linkiewicz, H. Meissner, and D. Dahlke. "RECONSTRUCTING BUILDINGS WITH DISCONTINUITIES AND ROOF OVERHANGS FROM OBLIQUE AERIAL IMAGERY." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-1/W1 (May 31, 2017): 465–71. http://dx.doi.org/10.5194/isprs-archives-xlii-1-w1-465-2017.

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This paper proposes a two-stage method for the reconstruction of city buildings with discontinuities and roof overhangs from oriented nadir and oblique aerial images. To model the structures the input data is transformed into a dense point cloud, segmented and filtered with a modified marching cubes algorithm to reduce the positional noise. Assuming a monolithic building the remaining vertices are initially projected onto a 2D grid and passed to RANSAC-based regression and topology analysis to geometrically determine finite wall, ground and roof planes. If this should fail due to the presence of discontinuities the regression will be repeated on a 3D level by traversing voxels within the regularly subdivided bounding box of the building point set. For each cube a planar piece of the current surface is approximated and expanded. The resulting segments get mutually intersected yielding both topological and geometrical nodes and edges. These entities will be eliminated if their distance-based affiliation to the defining point sets is violated leaving a consistent building hull including its structural breaks. To add the roof overhangs the computed polygonal meshes are projected onto the digital surface model derived from the point cloud. Their shapes are offset equally along the edge normals with subpixel accuracy by detecting the zero-crossings of the second-order directional derivative in the gradient direction of the height bitmap and translated back into world space to become a component of the building. As soon as the reconstructed objects are finished the aerial images are further used to generate a compact texture atlas for visualization purposes. An optimized atlas bitmap is generated that allows perspectivecorrect multi-source texture mapping without prior rectification involving a partially parallel placement algorithm. Moreover, the texture atlases undergo object-based image analysis (OBIA) to detect window areas which get reintegrated into the building models. To evaluate the performance of the proposed method a proof-of-concept test on sample structures obtained from real-world data of Heligoland/Germany has been conducted. It revealed good reconstruction accuracy in comparison to the cadastral map, a speed-up in texture atlas optimization and visually attractive render results.

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Peng, Shaohu, Weiqiang Su, Xiao Hu, Changhong Liu, Yuan Wu, and Hyundo Nam. "Subpixel Edge Detection Based on Edge Gradient Directional Interpolation and Zernike Moment." DEStech Transactions on Computer Science and Engineering, csse (July 24, 2018). http://dx.doi.org/10.12783/dtcse/csse2018/24488.

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Lu, Shengfang, Zhen Liu, Ye Chen, and Yang Gao. "A novel subpixel edge detection method of pantograph slide in complicated surroundings." IEEE Transactions on Industrial Electronics, 2021, 1. http://dx.doi.org/10.1109/tie.2021.3062276.

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Yang, Rui, Hanming Guo, Zhentao Chen, and Jiuai Sun. "Adaptive Subpixel Edge Detection for Locating the Center of Nut Screw Hole." International Journal of Precision Engineering and Manufacturing, May 26, 2021. http://dx.doi.org/10.1007/s12541-021-00544-8.

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Chang, Ren-Jung, and Jun-Fu Liu. "Model-Based Coarse-Fine Virtual Calibration and Visual Servo for Augmented Reality-Assisted Peg-in-Hole Microassembly." Journal of Micro and Nano-Manufacturing 6, no. 4 (October 16, 2018). http://dx.doi.org/10.1115/1.4041531.

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A three-dimensional (3D)-virtual calibration and visual servo are implemented for augmented reality (AR)-assisted peg-in-hole microassembly operations. By employing 3D model and ray casting, the 3D coordinates on virtual mating rod correspondent to the two-dimensional (2D) virtual image points are extracted. The detecting and tracking of image feature points for calibration is carried out by the proposed algorithm of regional template matching (TM) and scanning with edge fitting (RTM-SEF). For achieving subpixel error between the feature points in real and virtual images, a coarse-fine virtual calibration method is proposed. In regard to the image viewed by the real and virtual cameras, a calibrated virtual camera is utilized to track the mating rod. A visual servo control law including coarse and fine tuning is proposed to ensure sub-pixel error between the most important feature point in the real and virtual images. The AR technology is mainly employed in the alignment between micropeg and mating hole for inserting a micropeg of diameter 80 μm with length 1–1.4 mm into a mating rod with 100 μm hole.

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