A New Cooperative Algorithm Based on Artificial Fish Swarm Algorithm and K-means for Image Segmentation

سال انتشار: 1392
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 1,743

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شناسه ملی سند علمی:

CECIT01_719

تاریخ نمایه سازی: 14 شهریور 1392

چکیده مقاله:

Image Segmentation is one of the most important techniques in graphic and image processing. Most of image segmentation methods are based on clustering algorithms. Dataclustering is an unsupervised classification technique and belongs to NP-hard problems. One of the methods for solvingNP-hard problems is applying swarm intelligence algorithms. Artificial fish swarm algorithm (AFSA) is one of the swarm intelligence algorithms which is working based on populationand random search. In this paper, a new cooperative algorithm based on AFSA and k-means is proposed for performing imagesegmentation based on multi-level thresholding. The proposed algorithm utilizes both global search ability of AFSA and localsearch ability of k-means. The proposed algorithm along with some other known algorithms has been applied for segmenting famous images and their efficiency has been compared with each other. Experimental results comparison shows acceptable efficiency of the proposed algorithm.

کلیدواژه ها:

image segmentation ، data clustering ، artificial fish swarm algorithm ، k-means ، multilevel thresholding

نویسندگان

Shima Farshchian Yazdi

Department of Computer Engineering, Mashhad Branch, Islamic Azad University, Mashhad, Iran,

Milad Soltany

Department of Computer Engineering, Torbat-e-Jam Branch, Islamic Azad University, Torbat-e-Jam, Iran,

Mohammad Reza Meybodi

Department of Computer Engineering and Information Technology, Amirkabir University of Technology, Tehran,

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