Illumination-Invariant Image Matching Based on Simulated Kalman Filter (SKF) Algorithm - Nurnajmin Qasrina, Ann; Pebrianti, Dwi; Zuwairie, Ibrahim; Mohd Falfazli, Mat Jusof; Luhur, Bayuaji; Nor Rul Hasma, Abdullah (Universiti Teknikal Malaysia Melaka (UTeM), 2018)
In this paper, a novel image template matching approach to tackle illumination-invariant problem has been proposed. In order, the traditional algorithm to solve image matching problem take a lot of memory and computational time, image matching problem is assigned to optimization problem and can be solve precisely. Although recently some methods are presented for image matching illumination-invariant, all of them have the limitation in terms of dealing with the pixels complexity and many unknown parameters in the certain algorithm. The search of the image template has been performed exhaustively by using Simulated Kalman Filter (SKF) algorithm. The experiment is conducted using an image taken from the database and the contrast image changed to get the illumination effect. Experimental results show the comparison between SKF and Particle Swarm Optimization (PSO) to get the performance of the correct matching. The percentage of matching result for the image within six conditions are 24%, 16%, 16%, 12%, 28% and 4% accordingly which is higher than PSO algorithm, which is 0% correct matching for all conditions.