Date of Submission

Summer 7-29-2016

Degree Type

Thesis

Degree Name

Master of Science in Computer Science (MSCS)

Department

Computer Science

Track

Others

Computer Vision

Faculty Advisor

Chih-Cheng Hung

Chair

Frank Tsui

Committee Member

Jeffrey Chastine

Committee Member

Chia-Tien Dan Lo

Abstract

This thesis presents color image segmentation as a vital step of image analysis in computer vision. A survey of the Markov Random Field (MRF) with four different implementation methods for its parameter estimation is provided. In addition, a survey of swarm intelligence and a number of swarm based algorithms are presented. The MRF model is used for color image segmentation in the framework. This thesis introduces a new image segmentation implementation that uses the bee algorithm as an optimization tool in the Markovian framework. The experiments show that the new proposed method performs faster than the existing implementation methods with about the same segmentation accuracy.

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