A sub-pixel edge detection algorithm based on Zernike moments

REFERENCES

• Fraser CS. Innovation in automation for vision metrology system. Photogramm. Rec., 1997, 90, 901–911.
   Google Scholar
• Kayahan E, Oktem H, Hacizade F, Nasibov H, Gundogdu O. Measurement of surface roughness of metals using binary speckle image analysis. Tribol. Int., 2010, 43, 307–311.
   Web of Science ®Google Scholar
• Tabatabai AJ, Mitchell OR. Edge location to sub-pixel values in digital imagery. IEEE Trans. Pattern Anal. Mach. Intell., 1984, 6, 188–201.
   PubMed Web of Science ®Google Scholar
• Sundaram R. Analysis and implementation of an efficient edge detection algorithm. Opt. Eng., 2003, 42, 642–650.
   Web of Science ®Google Scholar
• Hu MK. Visual pattern recognition by moment invariants. IRE Trans. Inf. Theory, 1962, 8, 179–187.
   Web of Science ®Google Scholar
• Papakostas GA, Boutalis YS, Karras DA, Mertzios BG. A new class of Zernike moments for computer vision applications. Inf. Sci., 2007, 177, 2802–2819.
   Web of Science ®Google Scholar
• Gu J, Shu HZ, Toumoulin C, Luo LM. A novel algorithm for fast computation of Zernike moments. Pattern Recognit., 2002, 35, 2905–2911.
   Web of Science ®Google Scholar
• Yang ZW, Fang T. On the accuracy of image normalization by Zernike moments. Image Vis. Comput., 2010, 28, 403–413.
   Web of Science ®Google Scholar
• Ghosal S, Mehrotra R. Orthogonal moment operators for sub-pixel edge detection. Pattern Recognit., 1993, 26, 295–306.
   Web of Science ®Google Scholar
• Ye B, Peng J.-X. Invariance analysis of improved Zernike moments.J. Opt. A: Pure Appl. Opt., 2002, 4, 606–614.
   Google Scholar
• Papakostas GA, Boutalis YS, Papaodysseus CN, Fragoulis DK. Numerical error analysis in Zernike moments computation. Image Comput. Vis., 2006, 24, 960–969.
   Web of Science ®Google Scholar
• Belkasim SO, Ahmadi M, Shridhar M. Efficient algorithm for fast computation of Zernike moments. J. Franklin Inst., 1996, 333, 577–581.
   Web of Science ®Google Scholar
• Prata A, Rusc WV. Th. Algorithm for computation of Zernike polynomials expansion coefficients. Appl. Opt., 1989, 28, 749–754.
   PubMed Web of Science ®Google Scholar
• Sluzek A. On moment-based local operators for detecting image patterns. Image Vis. Comput., 2005, 23, 287–298.
   Web of Science ®Google Scholar
• Chong CW, Raveendran P, Mukundan R. A comparative analysis of algorithms for fast computation of Zernike moments. Pattern Recognit., 2003, 36, 731–742.
   Web of Science ®Google Scholar
• Fu B, Liu L.-Y, Quan Y, Zhang G.-J; Liu, J. Modified q-recursive algorithm for fast computing Zernike moments. Comput. Eng., 2008, 34, 7–9.
   Google Scholar
• Qu Y.-D, Cui C.-S, Chen S.-B, Li J.-Q. A fast subpixel edge detection method using Sobel–Zernike moments operator. Image Vis. Comput., 2005, 23, 11–17.
   Web of Science ®Google Scholar
• Truchetet F, Laligant O. Subpixle edge detection for dimensional control by artificial vision. J. Electron. Imag., 2001, 10, 234–239.
   Web of Science ®Google Scholar
• Serra J. Image analysis and Mathematical Morphology, 1982 (Academic Press, London).
   Google Scholar
• Wood SL, Qu GY. A modified gray level morphological gradient with accurate orientation estimates and reduced noise sensitivity, Proc. IEEE Conf. on Signals, systems and computers, Pacific Grove, CA, USA, October–November 2000, Vol. 2, IEEE, pp. 926–930.
   Google Scholar
• Teague M. Image analysis via the general theory of moments. J. Opt. Soc. Am., 1980, 70, 920–930.
   Web of Science ®Google Scholar
• Martín JAH, Santos M, de Lope J. Orthogonal variant moments features in image analysis. Inf. Sci., 2009, 180, 846–860.
   Web of Science ®Google Scholar
• Cui JW, Tan JB, Zhou Y, Zhang H. Improvement of vision measurement accuracy using Zernike moment based edge location error compensation model. J. Phys.: Conf. Ser., 2006, 48, 1353–1360.
   Google Scholar
• Nissinen A, Heikkinen LM, Kolehmainen V, Kaipio JP. Compensation of errors due to discretization, domain truncation and unknown contact impedances in electrical impedance tomography. Meas. Sci. Technol., 2009, 20, 105504.
   Web of Science ®Google Scholar
• Zhang L, Wu XQ, Hu XY. Research on CCD noise signal processing, Proc. 3rd Int. Conf. on Natural computation: ICNC ’07, Haikou, China, August 2007, Vol. 3, IEEE Computer Society, pp. 155–158.
   Google Scholar
• Shang YY, Zhang J, Guan Y, Zhang WG, Pan W, Liu H. Design and evaluation of a high-performance charge coupled device camera for astronomical imaging. Meas. Sci. Technol., 2009, 20, 104002.
   Web of Science ®Google Scholar
• Singh C, Walia E. Algorithms for fast computation of Zernike moments and their numerical stability. Image Vis. Comput., 2011, 29, 251–259.
   Web of Science ®Google Scholar