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Partial Shape Classification Using Contour Matching in Distance Transformation
November 1990 (vol. 12 no. 11)
pp. 1072-1079

An algorithm is presented to recognize and locate partially distorted 2D shapes without regard to their orientation, location, and size. The algorithm first calculates the curvature function from the digitized image of an object. The points of local maxima and minima extracted from the smooth curvature are used as control points to segment the boundary and to guide the boundary-matching procedure. The boundary-matching procedure considers two shapes at a time, one shape from the template databank, and the other from the object being classified. The procedure tries to match the control points in the unknown shape to those of a shape from the template databank, and estimates the translation, rotation, and scaling factors to be used to normalize the boundary of the unknown shape. The chamfer 3/4 distance transformation and a partial distance measurement scheme constitute the final step in measuring the similarity between the two shapes. The unknown shape is assigned to the class corresponding to the minimum distance. The algorithm has been successfully tested on partial shapes using two sets of data, one with sharp corners and the other with curve segments. This algorithm not only is computationally simple, but also works reasonably well in the presence of a moderate amount of noise.

[1] H. G. Barrow, J. M. Tenenbaum, and H. C. Wolf, "Parametric correspondence and chamfer matching: Two new techniques for image matching," inProc. 5th Int. Joint Conf. Artificial Intell., 1977, pp. 659-663.
[2] R. C. Bolles and R. A. Cain, "Recognizing and locating partial visible objects: The local-feature-focus method," inRobot Vision, A. Pugh, Ed., 1984.
[3] G. Borgefors, "Distance transformations in digital images,"Comput. Vision, Graphics, Image Processing, vol. 34, pp. 334-371, 1986.
[4] G. Borgefors, "An improved version of the chamfer matching algorithm," inProc. Int. Conf. Pattern Recognition, 1984.
[5] G. Borgefors, "Hierarchical chamfer matching: A parametric edge matching algorithm,"IEEE Trans. Pattern Anal. Machine Intell., vol. 10, pp. 849-865, Nov. 1988.
[6] J. F. Canny, "Finding lines and edges in images," M.S. thesis, Massachusetts Inst. Technol., Cambridge, 1983.
[7] P. E. Daniellson, "Euclidean distance mapping,"Comput. Vision, Graphics, Image Processing, vol. 14, pp. 227-248, 1980.
[8] J. W. Gorman, O. R. Mitchell, and F. P. Kuhl, "Partial shape recognition using dynamic programming,"IEEE Trans. Pattern Anal. Machine Intell., vol. 10, pp. 257-266, Mar. 1988.
[9] T. A. Gorgan, "Shape recognition and description: A comparative study," Ph.D. dissertation, Purdue Univ., West Lafayette, IN, 1983.
[10] L. Gupta, "Contour transformations for shape classification," Ph.D. dissertation, Southern Methodist Univ., Dallas, TX, 1986.
[11] T. F. Knoll and R. C. Jain, "Recognizing partially visible objects using feature indexed hypotheses,"IEEE J. Robotics Automat., vol. 2, pp. 3-13, Mar. 1986.
[12] C.C. Lin and R. Chellappa, "Classification of Partial 2-D Shapes Using Fourier Descriptors,"IEEE Trans. Pattern Analysis and Machine Intelligence, Vol. PAMI-9, No. 5, Sept. 1987, pp. 686-690.
[13] O. R. Mitchell and T. A. Gorgan, "Global and partial shapes discrimination for computer vision,"Opt. Eng., vol. 23, no. 5, pp. 484-491, 1984.
[14] W. A. Perkins, "A model-based vision system for industrial parts,"IEEE Trans. Comput., vol. C-27, pp. 126-143, Feb. 1978.
[15] K. E. Price, "Matching closed contours," inProc. IEEE 1984 Workshop Comput. Vision, 1984, pp. 130-134.
[16] P. F. Singer and R. Chellappa, "Machine perception of partially specified planar shapes," inProc. IEEE Conf. Comput. Vision Pattern Recognition, 1985.
[17] Y. J. Tejwani and R. A. Jones, "Machine recognition of partial shapes using feature vectors,"IEEE Trans. Syst., Man, Cybern., vol. SMC-12, pp. 504-516, July/Aug. 1985.

Index Terms:
partial shape classification; local minima; boundary segmentation; translation estimation; rotation estimation; scaling factor estimation; boundary normalisation; contour matching; distance transformation; 2D shapes; curvature function; digitized image; local maxima; boundary-matching; chamfer 3/4 distance transformation; partial distance measurement; sharp corners; curve segments; noise; pattern recognition; picture processing
H.C. Liu, M.D. Srinath, "Partial Shape Classification Using Contour Matching in Distance Transformation," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 12, no. 11, pp. 1072-1079, Nov. 1990, doi:10.1109/34.61706
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