Real-time object subspace searching based on discrete searching paths and local energy

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• 作者：Wen-Ju Zhou ; Zi-Xiang Fei ; Huo-Sheng Hu…
• 关键词：Real ; time ; object subspace ; discrete paths ; fast match ; level set ; local energy function
• 刊名：International Journal of Automation and Computing
• 出版年：2016
• 出版时间：April 2016
• 年：2016
• 卷：13
• 期：2
• 页码：99-107
• 全文大小：1,817 KB
• 参考文献：[1]W. J. Zhou, M. R. Fei, H. Y. Zhou, K. Li. A sparse representation based fast detection method for surface defect detection of bottle caps. Neurocomputing, vol. 123, pp. 406–414, 2014.CrossRef
  [2]H. Wang, W. Mou, G. Seet, M. H. Li, M. W. S. Lau, D. W. Wang. Real-time visual odometry estimation based on principal direction detection on ceiling vision. International Journal of Automation and Computing, vol. 10, no. 5, pp. 397–404, 2013.CrossRef
  [3]E. M. Hemerly. Automatic georeferencing of images acquired by UAV’s. International Journal of Automation and Computing, vol. 11, no. 4, pp. 347–352, 2014.CrossRef
  [4]M. Kass, A. Witkin, D. Terzopoulos. Snakes: Active contour models. International Journal of Computer Vision, vol. 1, no. 4, pp. 321–331. 1988.CrossRef MATH
  [5]T. F. Chan, L. A. Vese. Image Segmentation Using Level Sets and the Piecewise-constant Mumford-Shah Model, Technical Report 0014, Computational Applied Math Group, USA, 2000.
  [6]A. Tsai, A. Yezzi Jr, A. S. Willsky. Curve evolution implementation of the Mumford-Shah functional for image segmentation, denoising, interpolation, and magnification. IEEE Transactions on Image Processing, vol. 10, no. 8, pp. 1169–1186, 2001.CrossRef MATH
  [7]T. Chan, L. Vese. An active contour model without edges. In Proceedings of the 2nd International Conference, Scale- Space Theories in Computer Vision, Lecture Notes in Computer Science, Springer, Greece, vol. 1682, pp. 141–151, 1999.CrossRef
  [8]H. Y. Zhou, Y. Yuan, F. Q. Lin, T. W. Liu. Level set image segmentation with Bayesian analysis. Neurocomputing, vol. 71, no. 10–12, pp. 1994–2000, 2008.CrossRef
  [9]S. D. S. Al-Shaikhli, M. Y. Yang, B. Rosenhahn. Medical image segmentation using multi-level set partitioning with topological graph prior. In Proceedings of Image and Video Technology–PSIVT 2013 Workshops, Lecture Notes in Computer Science, Springer, Berlin, Heidelberg, Germany, vol. 8334, pp. 157–168, 2014.CrossRef
  [10]X. F. Ji, Q. Q. Wu, Z. J. Ju, Y. Y. Wang. Study of human action recognition based on improved Spatio-temporal features. International Journal of Automation and Computing, vol. 11, no. 5, pp. 500–509, 2014.CrossRef
  [11]S. Osher, J. A. Sethian. Fronts propagating with curvaturedependent speed: Algorithms based on Hamilton-Jacobi formulations. Journal of Computational Physics, vol. 79, no. 1, pp. 12–49, 1988.MathSciNet CrossRef MATH
  [12]J. A. Sethian. A fast marching level set method for monotonically advancing fronts. Proceedings of the National Academy of Sciences of the United States of America, vol. 93, no. 4, pp. 1591–1595, 1996.MathSciNet CrossRef MATH
  [13]Y. H. R. Tsai. Rapid and accurate computation of the distance function using grids. Journal of Computational Physics, vol. 178, no. 1, pp. 175–195, 2002.MathSciNet CrossRef MATH
  [14]D. L. Chopp. Computing minimal surfaces via level set curvature flow. Journal of Computational Physics, vol. 106, no. 1, pp. 77–91, 1993.MathSciNet CrossRef MATH
  [15]D. Adalsteinsson, D. Adalsteinsson, J. A. Sethian, J. A. Sethian. A fast level set method for propagating interfaces. Journal of Computational Physics, vol. 116, pp. 269–277, 1994.MathSciNet MATH
  [16]D. Mumford, J. Shah. Optimal approximations by piecewise smooth functions and associated variational problems. Communications on Pure and Applied Mathematics, vol. 42, no. 5, pp. 577–685, 1989.MathSciNet CrossRef MATH
  [17]T. F. Chan, L. A. Vese. Active contours without edges. IEEE Transactions on Image Processing, vol. 10, no. 2, pp. 266–277, 2001.CrossRef MATH
  
• 作者单位：Wen-Ju Zhou (1) (2)
  Zi-Xiang Fei (1)
  Huo-Sheng Hu (1)
  Li Liu (2)
  Jing-Na Li (2)
  Peter James Smith (3)
  
  1. School of Computer Science and Electronic Engineering, University of Essex, Colchester, CO4 3SQ, UK
  2. School of Information and Electronic Engineering, Ludong University, Yantai, 264025, China
  3. Vitec Videocom Ltd, Bury St Edmunds, Suffolk, IP33 3TB, UK
  
• 刊物类别：Engineering
• 刊物主题：Automation and Robotics
  Computer Applications
  Computer-Aided Engineering and Design
  Chinese Library of Science
  
• 出版者：Institute of Automation, Chinese Academy of Sciences, co-published with Springer-Verlag GmbH
• ISSN：1751-8520

文摘

In automatic visual inspection, the object image subspace should be segmented and matched quickly so that the affine relationship can be built between the template image and the sample image. When the interference is strong and the illumination is uneven, for example in an industrial application, this can make it difficult to obtain an objects subspace quickly and accurately in real-time. In this paper, a novel strategy is proposed to adopt discrete radial search paths instead of searching all points in an image. Therefore, the searching time can be substantially reduced. In order to reduce the influence coming from the industrial environment, the paper proposes another method that is local energy level set segmentation, which can locate the object subspace more efficiently and accurately. The detection of “crown caps” is presented as an example in this paper. Detection effects and computing time are compared between several detection methods, and the mechanisms of inspection have also been analyzed.