@inproceedings{02d421aeb4714c7984cce7e654343dd7,
title = "Curvature estimation and unique corner point detection for boundary representation",
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.",
author = "Kwanghoon Sohn and Alexander, {Winser E.} and Kim, {Jung H.} and Yonghoon Kim and Snyder, {Wesley E.}",
year = "1992",
language = "English",
isbn = "0818627204",
series = "Proceedings - IEEE International Conference on Robotics and Automation",
publisher = "Publ by IEEE",
pages = "1590--1595",
booktitle = "Proceedings - IEEE International Conference on Robotics and Automation",
note = "Proceedings of the 1992 IEEE International Conference on Robotics and Automation ; Conference date: 12-05-1992 Through 14-05-1992",
}