Color Image Segmentation Using the Bee Algorithm in the Markovian Framework

<p>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.</p>

Name thesis:degree_name

Master of Science in Computer Science (MSCS)

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Computer Science

Year dc:date.available

2016

Author dc:creator

• Dragaj, Vehbi

Contributors dc:contributor

• Chih-Cheng Hung
• Frank Tsui
• Jeffrey Chastine

• Image segmentation
• Markov Random Field
• The Bees Algorithm
• Other Computer Sciences

Repository record dc:identifier

https://digitalcommons.kennesaw.edu/cs_etd/5

OAI identifier oai:identifier

oai:digitalcommons.kennesaw.edu:cs_etd-1005