Optimization of focus measure using Genetic Algorithm

摘要

This paper presents the use of Genetic Algorithm as a search method for focus measure in Shape From Focus(SFF). Previous methods compute focus value for each pixel locally by summing all values within a small window.This summation is a good approximation of focus quality, but is not optimal one. The Genetic Algorithm is usedas a fine tuning process in which a measure of best focus is used as the fitness function corresponding to motionparameter values which make up each gene. The experimental results show that the proposed method performsbetter than previous algorithms such as Sum of the Modified Laplacian(SML), Grey Level Variance(GLV) andTenenbaum Focus Measure. The results are compared using root mean square error(RMSE) and correlation.The experiments are conducted using objects simulated cone, real cone and TFT-LCD color filter~1 to evaluateperformance of the proposed algorithm.