A Computational Approach to Boundary Detection
Abstract
A unified approach to boundary perception is presented. The model consists of a hierarchical system which extracts and groups salient features in the image at different spatial scales. In the first stage a Gabor wavelet decomposition provides a representation of the image which is orientation selective, has optimal localization properties, and provides a good model for early feature detection. Following this, local competitive interactions are introduced which help in reducing the effects of noise and illumination variations. Scale interactions help in localizing line ends and corners, and play an important role in boundary perception. The final stage groups similar features aiding in boundary completion. Experimental results on detecting edges, texture boundaries, and illusory contours are provided.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Cite
Text
Manjunath and Chellappa. "A Computational Approach to Boundary Detection." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1991. doi:10.1109/CVPR.1991.139716Markdown
[Manjunath and Chellappa. "A Computational Approach to Boundary Detection." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1991.](https://mlanthology.org/cvpr/1991/manjunath1991cvpr-computational/) doi:10.1109/CVPR.1991.139716BibTeX
@inproceedings{manjunath1991cvpr-computational,
title = {{A Computational Approach to Boundary Detection}},
author = {Manjunath, B. S. and Chellappa, Rama},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
year = {1991},
pages = {358-363},
doi = {10.1109/CVPR.1991.139716},
url = {https://mlanthology.org/cvpr/1991/manjunath1991cvpr-computational/}
}