Share Email Print
cover

Proceedings Paper

Segmentation of color images using genetic algorithm with image histogram
Author(s): P. Sneha Latha; Pawan Kumar; Samruddhi Kahu; Kishor M. Bhurchandi
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

This paper proposes a family of color image segmentation algorithms using genetic approach and color similarity threshold in terns of Just noticeable difference. Instead of segmenting and then optimizing, the proposed technique directly uses GA for optimized segmentation of color images. Application of GA on larger size color images is computationally heavy so they are applied on 4D-color image histogram table. The performance of the proposed algorithms is benchmarked on BSD dataset with color histogram based segmentation and Fuzzy C-means Algorithm using Probabilistic Rand Index (PRI). The proposed algorithms yield better analytical and visual results.

Paper Details

Date Published: 14 February 2015
PDF: 5 pages
Proc. SPIE 9445, Seventh International Conference on Machine Vision (ICMV 2014), 94450M (14 February 2015); doi: 10.1117/12.2180559
Show Author Affiliations
P. Sneha Latha, Visvesvaraya National Institute of Technology (India)
Pawan Kumar, Visvesvaraya National Institute of Technology (India)
Samruddhi Kahu, Visvesvaraya National Institute of Technology (India)
Kishor M. Bhurchandi, Visvesvaraya National Institute of Technology (India)


Published in SPIE Proceedings Vol. 9445:
Seventh International Conference on Machine Vision (ICMV 2014)
Antanas Verikas; Branislav Vuksanovic; Petia Radeva; Jianhong Zhou, Editor(s)

© SPIE. Terms of Use
Back to Top