Comparison of three-color image segmentation algorithms in four color spaces

John M. Gauch; Chi Wan Hsia

doi:10.1117/12.131388

1 November 1992 Comparison of three-color image segmentation algorithms in four color spaces

John M. Gauch, Chi Wan Hsia

Proceedings Volume 1818, Visual Communications and Image Processing '92; (1992) https://doi.org/10.1117/12.131388
Event: Applications in Optical Science and Engineering, 1992, Boston, MA, United States

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.

Citation Download Citation

John M. Gauch and Chi Wan Hsia "Comparison of three-color image segmentation algorithms in four color spaces", Proc. SPIE 1818, Visual Communications and Image Processing '92, (1 November 1992); https://doi.org/10.1117/12.131388

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