Curvature estimation and unique corner point detection for boundary representation

Kwanghoon Sohn, Winser E. Alexander, Jung H. Kim, Yonghoon Kim, Wesley E. Snyder

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

Computing a curvature function on a digitized boundary is an ill-posed problem due to the discrete nature of the boundary. The authors use a constrained regularization technique to obtain the optimal smooth boundary before computing the curvature function. A corner sharpness is defined for robust corner point detection. Matching results in the presence of occlusion using a 2-D Hopfield neural network are also shown to produce excellent results using this boundary representation. The human cognition system recognizes both ideal corner points and slightly rounded segments as corner points. A criterion to mimic a human's capability of detecting corner points and to compensate for the smoothing effect of the preprocessing in detecting corner points in the curvature function space is established.

Original languageEnglish
Title of host publicationProceedings - IEEE International Conference on Robotics and Automation
PublisherPubl by IEEE
Pages1590-1595
Number of pages6
Volume2
ISBN (Print)0818627204
Publication statusPublished - 1992 Dec 1
EventProceedings of the 1992 IEEE International Conference on Robotics and Automation - Nice, Fr
Duration: 1992 May 121992 May 14

Other

OtherProceedings of the 1992 IEEE International Conference on Robotics and Automation
CityNice, Fr
Period92/5/1292/5/14

All Science Journal Classification (ASJC) codes

  • Engineering(all)

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  • Cite this

    Sohn, K., Alexander, W. E., Kim, J. H., Kim, Y., & Snyder, W. E. (1992). Curvature estimation and unique corner point detection for boundary representation. In Proceedings - IEEE International Conference on Robotics and Automation (Vol. 2, pp. 1590-1595). Publ by IEEE.