圖形比對領域由於應用範圍很廣泛，成為近年來機械視覺領域中十分熱門的一項研究題目。目前圖形比對所遭遇到主要的問題點在於：難以同時達到效率、旋轉不變量與物件缺陷的強健性三者之間的平衡與需求。
本論文從環形編碼出發，對既有的環狀樣板比對技術加以改進，發展出一套新的串列比對方法。利用此串列比對法搭配既有之環形編碼與環狀樣板加以改進之後，成功地突破了以往在樣板圖形比對之研究中，對於比對效率、旋轉不變量與物件缺陷的強健性三者往往無法同時兼顧的問題。並且利用邊跡影像進行輸入，改善原本利用全域閥值之二值化前處理，使得灰階影像因明暗變化過劇，無法將待測物自背景分離因而無法進行比對之限制。
最後，本論文會整合出一套完整的圖形比對演算法，並且依次以不同複雜度的影像進行模擬以檢視之。以驗證所提出之演算法的確具有圖形比對－包含位置以及旋轉角、旋轉不變量特性以及忍受待測物具有受到遮蔽以及雜邊跡侵入等缺陷之強健性等能力。

[1] A.k. Jain, R.P. W. Duin and J.C. Mao, “Statistical pattern recognition : A review,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 22, no.1, pp.4-37, 2000.
[2] R. Bajcsy and S. Kovacic, “Multiresolution elastic matching,” Computer Vision Graphics Image Processing, vol.46, pp.1-21, 1989.
[3] U. Grenender, General Pattern Theory. Oxford Univ. Press, 1993.
[4] H.L. Peng and S.Y. Chen, “Trademark shape recognition using closed contours,” Pattern Recognition, vol.18, pp.791-803, 1997.
[5] L.I. Perlovsky, “Conundrum of combinational complexity,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.20, no.6, pp.666-670, 1998.
[6] R.O. Duda and P.E. Hart, Pattern Classification and Scene Analysis. Wiley, New York, 1972.
[7] K. Fukunaga, Introduction to Statistical Pattern Recognition. Academic Press, Boston, 1990.
[8] A.K. Jain, J. Mao, and K.M. Mohiuddin, “Artificial neural networks: A tutorial,” Computer, pp31-44, 1996.
[9] S. Haykin, Neural Networks: A Comprehensive Foundation. Prentice-Hall, New Jersey, 1999.
[10] 彭國軒，快速物件辨認與定位－環狀樣板比對，清華大學碩士論文， 2003.
[11] D.P. Huttenlocher, G.A. Klanderman, and W.J. Rucklidge, “Comparing images using the Hausdorff distance,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 15, no. 9, pp.850-863, 1993.
[12] D.P. Huttenlocher, R.H. Lilien, and C.F. Olson, “View-based recognition using an eigenspace approximation to the Hausdorff measure,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.21, no.9, 1999.
[13] Oh-Kyu Kwon, Dong-Gyu Sim and, Rae-Hong Park, “ Robust Hausdorff distance matching algorithms using pyramidal structures,” Pattern Recognition, vol.34, no.10, pp.2005-2013, 2001.
[14] Xilin Yi and Octavia I. Camps, “Line-based recognition using a multi-dimensional Hausdorff distance,” IEEE. Trans. on Pattern Analysis And Machine Intelligence, vol.21, no.9, pp.901-916, 1999.
[15] F. Stein and G. Medioni, “Structural indeing : efficient 2-D object recognition,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.14, no.12, pp.1198-1204, 1992.
[16] A.M. Mayez, “An efficient indexing scheme for image storage and recognition,” IEEE Transactions on Industrial Electronics, vol.46, no.2, pp.429–439, 1999.
[17] G. Cortelazzo, G.A. Mian, G. Vezzi, and P. Zamperoni, “Trademark shapes description by string-matching techniques,” Pattern Recognition, vol.27, no. 8, pp.1005–1018, 1994.
[18] H.L. Peng and S.Y. Chen, “Trademark shape recognition using closed contours,” Pattern Recognition Letters, vol.18, pp.791–803, 1997.
[19] C. Rekeczky, A. Ushida, and T. Roska, “Rotation invariant detection of moving and standing objects using analogic neural network algorithms based on ring,” IEICE Transactions on Fundamentals, vol.E78-A, no.10, pp.1316–1329, 1995.
[20] L.A. Torres-Méndez, J.C. Ruiz-Suárez, Luis E. Sucar, and G. Gómez, “Translation, rotation, and scale-Invariant object recognition,” IEEE Transactions on Systems, Man, and Cybernetics, vol.30, no.1, pp.125–130, 2000.
[21] A. Apostolico and Z. Galil, Pattern Matching Algorithms. Oxford University Press, 1997.
[22] H.J. Wolfson, “On curve matching,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 12, no.5, pp. 483–489, 1990.
[23] R.C. Gonzalez and R.E. Woods, Digital Image Processing. Prentice Hall, 2002.
[24] D. Ziou and S. Tabbone, “Edge detection techniques－An overview,” Image Recognition, Analysis, Understanding, and Processing Techniques, vol.8, pp.537-559, 1998.
[25] J. Canny, “A computational approach to edge detection,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.PAMI-8, no.6, pp.679-698, 1986.
[26] R.A. Wagner and M.J. Fischer, “The string-to-string correction problem,” Journal of the Association for Computing Machinery, vol.21, no.1, pp.168-173, 1974.
[27] W.H. Tsai and S.S. Yu, “Attributed string matching with merging for shape recognition,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.PAMI-7, no.4, pp.453-462, 1985.
[28] J. Lladós, H. Bunke, and E. Martí, “Finding rotational symmetries by cyclic string matching,” Pattern Recognition Letters, vol.18, pp. 1435-1442, 1997.
[29] Serkan Kaygin and M. Mete Bulut, “Shape recognition using attributed string matching with polygon vertices as the primitives,” Pattern Recognition Letters, vol.23, no.1-3, pp. 287-294, 2002.
[30] R.O. Duda and P.E. Hart, “Use of the Hough transformation to detect lines and curves in picture,” Commun. ACM, vol.15, no.1, pp.11-15, 1972.
[31] D.G. Sim and R.H. Park, “Two-dimensional object alignment based on the robust oriented Hausdorff similarity measure,” IEEE Transactions on Image Processing, vol.10, no.3, pp.475-483, 2001.
[32] 陳子超，表面黏著元件之光學檢測，清華大學碩士論文，2003.
[33] M. Sonka, V. Hlavac, and R. Boyle, Image Processing, Analysis, and Machine vision. PWS Publishing, 1999.
[34] B.K.P. Horn, Robot Vision. MIT Press, 1986.