Inteligencia artificial

Particle Swarm Optimization Methods for Pattern Recognition and Image Processing
by Mahamed G. H. Omran

Submitted in partial fulfillment of the requirements for the degree Philosophiae Doctor in the Faculty of Engineering, Built Environment and Information Technology University of Pretoria Pretoria November 2004

Particle Swarm Optimization Methods for Pattern Recognition and ImageProcessing
by Mahamed G. H. Omran

Abstract
Pattern recognition has as its objective to classify objects into different categories and classes. It is a fundamental component of artificial intelligence and computer vision. This thesis investigates the application of an efficient optimization method, known as Particle Swarm Optimization (PSO), to the field of pattern recognition and image processing.First a clustering method that is based on PSO is proposed. The application of the proposed clustering algorithm to the problem of unsupervised classification and segmentation of images is investigated. A new automatic image generation tool tailored specifically for the verification and comparison of various unsupervised image classification algorithms is then developed. A dynamic clusteringalgorithm which automatically determines the "optimum" number of clusters and simultaneously clusters the data set with minimal user interference is then developed. Finally, PSO-based approaches are proposed to tackle the color image quantization and spectral unmixing problems. In all the proposed approaches, the influence of PSO parameters on the performance of the proposed algorithms is evaluated.Key terms: Clustering, Color Image Quantization, Dynamic Clustering, Image Processing, Image Segmentation, Optimization Methods, Particle Swarm Optimization, Pattern Recognition, Spectral Unmixing, Unsupervised Image Classification.

Thesis supervisor: Prof. A. P. Engelbrecht Thesis co-supervisor: Dr. Ayed Salman
Department of Computer Engineering, Kuwait University, Kuwait

Department ofComputer Science Degree: Philosophiae Doctor ii

“Obstacles are those frightening things you see when you take your eyes off your goal.” Henry Ford

“You will recognize your own path when you come upon it, because you will suddenly have all the energy and imagination you will ever need.” Jerry Gillies

iii

Acknowledgments

I address my sincere gratitude to God as whenever I faced anydifficulty I used to pray to God to help me and He always was there protecting and saving me. Then, I would like to express my warm thanks to Professor Andries Engelbrecht, who spared no effort in supporting me with all care and patience. I enjoyed working with him, making every moment I spent in the research work as enjoyable as can be imagined. I would like also to thank my co-supervisor Dr. AyedSalman from Kuwait University for his continuous guidance, encouragement and patience throughout the PhD journey. I will never forget the long hours we spent together discussing various ideas and methods. Last but not least, I would love to thank my family for their support and care, especially my mother Aysha and my father Ghassib. May God bless and protect them both hoping that God will help me torepay them part of what they really deserve. I also thank my two sisters Ala'a and Esra'a for their help in preparing this thesis.

iv

Contents
Chapter 1 Introduction....................................................................................................................1 1.1Motivation............................................................................................................1 1.2 Objectives ............................................................................................................2 1.3 Methodology ........................................................................................................3 1.4 Contributions........................................................................................................4 1.5 Thesis...