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Proceedings Paper

Comparison of three-color image segmentation algorithms in four color spaces
Author(s): John M. Gauch; Chi Wan Hsia
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Paper Abstract

In this paper, we describe how three conventional segmentation methods can be generalized to handle color images. The segmentation algorithms we consider are: (1) seed based region growing, (2) directional derivative based edge detection, and (3) recursive split and merge. We then evaluate the effectiveness of these techniques using color difference metrics associated with four different color spaces and a variety of real and synthetic color images. The four color spaces we evaluate are: (1) the spectral primary system (RGB), (2) the NTSC transmission system (YIQ), (3) the hue saturation and brightness system (HLS), and (4) the CIE perceptually uniform space (LAB). We compare these segmentation results using real and synthetic color images which have been 'hand segmented' to determine true object boundaries.

Paper Details

Date Published: 1 November 1992
PDF: 14 pages
Proc. SPIE 1818, Visual Communications and Image Processing '92, (1 November 1992); doi: 10.1117/12.131388
Show Author Affiliations
John M. Gauch, Northeastern Univ. (United States)
Chi Wan Hsia, Northeastern Univ. (United States)

Published in SPIE Proceedings Vol. 1818:
Visual Communications and Image Processing '92
Petros Maragos, Editor(s)

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