Abstract
This paper presents a shape description method based on contour segment curvature (CSC). The CSC is defined as the ratio of the line length connecting two endpoints of a contour segment to its curve length. To extract consistent contour segment, the concept of overlapped contour segment is introduced. The rotation and scale invariant CSC can be extracted through the use of the overlapped contour segment. The proposed method describes the shape of objects with feature vectors that represents the distribution of the CSC, and measures the similarity by comparing the feature vector acquired from the corresponding unit-length segment. The experimental results show that the proposed method is not only invariant to rotation and scale but also superior to the NCCH and the TRP method in clustering power. Furthermore, the performance improvement is expected by adding the distance information to the CSC.
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References
Rui, Y., Huang, T.S., Chang, S.: Image Retrieval: Past, Present, and Future. Journal of Visual Communication and Image Representation 10, 1–23 (1999)
Safar, M., Shahabi, C., Sun, X.: Image Retrieval by Shape: A Comparative Study. In: Proc. of the IEEE International Conference on Multimedia and Expo., vol. (I), pp. 141–154 (2000)
Zhang, D., Lu, G.: Review of shape representation and description techniques. Pattern Recognition 37, 1–19 (2004)
Loncaric, S.: A Survey of Shape Analysis Techniques. Pattern Recognition 31(8), 983–1001 (1998)
Rui, Y., She, A.C., Huang, T.S.: A Modified Fourier Descriptors for Shape Matching in MARS. In: Image Databases and Multimedia Search. Series on Software Engineering and Knowledge Engineering, vol. 8, pp. 165–180. World scientific Publishing, Singapore (1998)
Flusser, J.: Fast calculation of geometric moments of binary images. In: Proc. of 22nd OAGM 1998 Workshop Pattern Recognition Medical Computer Vision, Illmitz, Austria, pp. 265–274 (1998)
Iivarinen, J., Visa, A.: Shape Recognition of Irregular Objects. In: Proc. of SPIE, vol. 2904, pp. 25–32 (1996)
Chang, C.C., Hwang, S.M., Buehrer, D.J.: A Shape Recognition Scheme Based on Relative Distances of Feature Points form the Centroid. Pattern Recognition 24(11), 1053–1063 (1991)
Tang, Y.Y., Cheng, H.D., Suen, C.Y.: Transformation-Ring-Projection(TRP) Algorithm and Its VLSI Implementation. In: Wang, P.S.P. (ed.) Character & Handwriting Recognition. World Scientific Series in Computer Science, vol. 30, pp. 25–56 (1991)
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© 2005 Springer-Verlag Berlin Heidelberg
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Kim, MK. (2005). Rotation and Scale Invariant Shape Description Using the Contour Segment Curvature. In: De Gregorio, M., Di Maio, V., Frucci, M., Musio, C. (eds) Brain, Vision, and Artificial Intelligence. BVAI 2005. Lecture Notes in Computer Science, vol 3704. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11565123_41
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DOI: https://doi.org/10.1007/11565123_41
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29282-1
Online ISBN: 978-3-540-32029-6
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