Multi-level Threshold Image Segmentation Using Artificial Bee Colony Algorithm

Image segmentation is still a crucial problem in image processing. In this paper, we proposed a novel multi-level image segmentation method based on PSNR using artificial bee colony algorithm (ABCA). PSNR is considered as an objective function of ABCA. The best multi-level thresholds (t 1 *,t 2 *,.....

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Bibliographic Details
Published in2013 Fifth International Conference on Measuring Technology and Mechatronics Automation pp. 707 - 711
Main Authors Hu Zhihui, Yu Weiyu, Lv Shanxiang, Feng Jiuchao
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.01.2013
Subjects
Entropy
Gaussian noise
Genetic algorithms
Image segmentation
Noise measurement
PSNR
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Summary:Image segmentation is still a crucial problem in image processing. In this paper, we proposed a novel multi-level image segmentation method based on PSNR using artificial bee colony algorithm (ABCA). PSNR is considered as an objective function of ABCA. The best multi-level thresholds (t 1 *,t 2 *,...,t n-1 *,t n *) are those which can make the PSNR maximize. Further, we compare entropy and PSNR in segmenting gray-level images and noisy images. Through experiments, it is found that the entropy isn't suitable to be applied to segmentation of images with Gaussian noise. So we can conclude that entropy can't be used for noisy image segmentation. The experiments results demonstrate our proposed method is effective and efficient.
ISBN:9781467356527
1467356522
ISSN:2157-1473
DOI:10.1109/ICMTMA.2013.177