Embedded Mutation Strategies in Particle Swarm Optimization for Solving Camera Calibration Problem

Abstract

Particle Swarm Optimization is a very effective Nature influenced innovation that relic widely used in solving many real-world problems over the years. This paper is an attempt to embed different mutation schemes in PSO and testing the different versions of PSO on camera calibration problem. One of the more challenging real-world issues in the realm of image processing is the calibration of cameras. The ideal parameter value for achieving the shortest pixel length is investigated in this research using the enlarged Particle Swarm Optimization approach. The results obtained in the empirical section of the paper suggest that PSO has proved to be a better version while embedding different mutation strategies for this problem.