1 November 1992 Comparison of three-color image segmentation algorithms in four color spaces
Author Affiliations +
Proceedings Volume 1818, Visual Communications and Image Processing '92; (1992); doi: 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.
© (1992) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
John M. Gauch, 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); doi: 10.1117/12.131388; https://doi.org/10.1117/12.131388
PROCEEDINGS
14 PAGES


SHARE
KEYWORDS
Image segmentation

Image processing

Image processing algorithms and systems

Edge detection

Roads

Detection and tracking algorithms

Image analysis

Back to Top