Edge detection by using edge density and eleven algorithm comparisons in three types of color images

W. X. Wang; J. Y. Xu

doi:10.1117/12.913593

24 January 2012 Edge detection by using edge density and eleven algorithm comparisons in three types of color images

W. X. Wang, J. Y. Xu

Proceedings Volume 8292, Color Imaging XVII: Displaying, Processing, Hardcopy, and Applications; 82921D (2012) https://doi.org/10.1117/12.913593
Event: IS&T/SPIE Electronic Imaging, 2012, Burlingame, California, United States

Abstract

Edge detection in grey scale image processing is a traditional research subject, but recently more and more researchers make efforts on the edge detection in color images. This paper presents a novel edge detection algorithm using the local, nonparametric estimation of the color image density. The method firstly analyses the edge shape information provided by the local probability distribution of the color image both in the horizontal and vertical directions respectively, then it obtains the modulus for the edge detection in the color image. With the increasing of window size, the other types of distributions can be simplified to the three types of the distributions presented in this study. In experiements, eleven different edge detection algorithms are compared for the three types of color images: smooth surface objects with a few edges; thin (or lines and curves) objects with many edges; and rough surface objects with more edges. And the algorithms include fractional, the first and the second order differential operators and other non-differential ones. Experiments show that the studied method is efficient.for edge extracting in a color image, and can give a satisfactory edge detection result in most cases.

Citation Download Citation

W. X. Wang and J. Y. Xu "Edge detection by using edge density and eleven algorithm comparisons in three types of color images", Proc. SPIE 8292, Color Imaging XVII: Displaying, Processing, Hardcopy, and Applications, 82921D (24 January 2012); https://doi.org/10.1117/12.913593

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