Application of Particle Swarm Optimization in Optimizing Stereo Matching Algorithm’s Parameters for Star Fruit Inspection System

• Main Authors: Nasroddin, Saidatul Nizan, Mohd Mokji, Musa, Tan, Kok, Zainal Abidin, Amar Faiz, Amirulah, Rahman, Nordin, Nur Anis, Hasim, Saipol Hadi, Zakaria, Hamzah, Hassan, Jefery, Jaafar, Hazriq Izzuan, Khairuddin, Osman
• Format: Conference or Workshop Item
• Language: English
• Published: 2014
• Subjects: TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://eprints.utem.edu.my/id/eprint/11672/1/2014_Conf._13Feb_ICRET2014_BATAM_%283%29.pdf; http://eprints.utem.edu.my/id/eprint/11672/

This paper reports the finding of the experimentation of the Particle Swarm Optimization in optimizing the stereo matching algorithm’s parameters for the star fruit inspection system. The star fruit inspection system is built by CvviP Universiti Teknologi Malaysia. While the stereo matching algorithm used in the experiment is taken from the Matlab library. Each particle of Particle Swarm Optimization in the search pace repsents a set of candidate numerical value of the stereo matching’s parameters. The fitness function for this application is the sum of absolute error of the gray scale value of both images. Based on this information, the particles will improve its position in the search space by moving towards its best record and the swarm best record. The process repeated until the maximum iteration met. The result indicates that there is potential application of Particle Swarm Optimization in stereo matching’s parameters tuning.