Optimal Corner Detector
Abstract
A corner is defined as the junction point of two or more straight line edges. Corners are special features in a image. They are of great use in computing the optical flow and structure from motion. In this paper, we report an optimal corner detector which uses a mathematical model for a corner. An optimal gray tone corner detector is derived for a restricted case of corners, i.e. corners made by lines which are symmetric about a horizontal axis. The resultant corner detector is described by product of sine in x and exponential in y direction in a portion of the mask and by the product of two sines in x and y directions in the remaining portion of it. It is then generalized to include any corner of an arbitrary angle and orientation. This results in an approximation of all corners by a total of twelve major types. It is observed that all the twelve masks can actually be configured with four smaller sub-masks, and this results in a significant reduction in the computetions. The computations are further reduced by using the the separability of masks. Results for synthetic and real scenes are reported.
Cite
Text
Rangarajan et al. "Optimal Corner Detector." IEEE/CVF International Conference on Computer Vision, 1988. doi:10.1109/CCV.1988.589975Markdown
[Rangarajan et al. "Optimal Corner Detector." IEEE/CVF International Conference on Computer Vision, 1988.](https://mlanthology.org/iccv/1988/rangarajan1988iccv-optimal/) doi:10.1109/CCV.1988.589975BibTeX
@inproceedings{rangarajan1988iccv-optimal,
title = {{Optimal Corner Detector}},
author = {Rangarajan, Krishnan and Shah, Mubarak and Van Brackle, David},
booktitle = {IEEE/CVF International Conference on Computer Vision},
year = {1988},
pages = {90-94},
doi = {10.1109/CCV.1988.589975},
url = {https://mlanthology.org/iccv/1988/rangarajan1988iccv-optimal/}
}