Title
Optimal Corner Detector
Keywords
Computer Science; Artificial Intelligence; Imaging Science; Photographic Technology
Abstract
A corner is defined as the junction point of two or more stright 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 the product of the sine in x and an exponential in the y direction in a portion of the mask and by the product of two sines in x and y directions in the remaining portion. 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 computations. The computations are further reduced by using the separability of masks. Results for synthetic and real scenes are reported.
Journal Title
Computer Vision Graphics and Image Processing
Volume
48
Issue/Number
2
Publication Date
1-1-1989
Document Type
Note
Language
English
First Page
230
Last Page
245
WOS Identifier
ISSN
0734-189X
Recommended Citation
Rangarajan, Krishnan; Shah, Mubarak; and Vanbrackle, David, "Optimal Corner Detector" (1989). Faculty Bibliography 1980s. 824.
https://stars.library.ucf.edu/facultybib1980/824
Comments
Authors: contact us about adding a copy of your work at STARS@ucf.edu