On the classification of image features

While the primary purpose of edge detection schemes is to be able to produce an edge map of a given image, the ability to distinguish between different feature types is also of importance. In this paper we examine feature classification based on local energy detection and show that local energy measures are intrinsically capable of making this classification because of the use of odd and even filters. The advantage of feature classification is that it allows for the elimination of certain feature types from the edge map, thus simplifying the task of object recognition.

[1]  J. Alison Noble,et al.  Finding Corners , 1988, Alvey Vision Conference.

[2]  D Marr,et al.  Theory of edge detection , 1979, Proceedings of the Royal Society of London. Series B. Biological Sciences.

[3]  J. Canny Finding Edges and Lines in Images , 1983 .

[4]  Svetha Venkatesh,et al.  Edge detection is a projection , 1989, Pattern Recognit. Lett..

[5]  R. Bracewell The Fourier Transform and Its Applications , 1966 .

[6]  Robyn A. Owens,et al.  Feature detection from local energy , 1987, Pattern Recognit. Lett..

[7]  D. Burr,et al.  Feature detection in human vision: a phase-dependent energy model , 1988, Proceedings of the Royal Society of London. Series B. Biological Sciences.