Optimization of focus measure using genetic algorithm

Ik-Hyun Lee; Muhammad Tariq Mahmood; Tae-Sun Choi

doi:10.1117/12.798209

15 September 2008 Optimization of focus measure using genetic algorithm

Ik-Hyun Lee, Muhammad Tariq Mahmood, Tae-Sun Choi

Proceedings Volume 7073, Applications of Digital Image Processing XXXI; 70731T (2008) https://doi.org/10.1117/12.798209
Event: Optical Engineering + Applications, 2008, San Diego, California, United States

Abstract

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 used as a fine tuning process in which a measure of best focus is used as the fitness function corresponding to motion parameter values which make up each gene. The experimental results show that the proposed method performs better than previous algorithms such as Sum of the Modified Laplacian(SML), Grey Level Variance(GLV) and Tenenbaum 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 filter¹ to evaluate performance of the proposed algorithm.

Citation Download Citation

Ik-Hyun Lee, Muhammad Tariq Mahmood, and Tae-Sun Choi "Optimization of focus measure using genetic algorithm", Proc. SPIE 7073, Applications of Digital Image Processing XXXI, 70731T (15 September 2008); https://doi.org/10.1117/12.798209

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KEYWORDS

Genetic algorithms

3D image processing

3D image reconstruction

Cameras

CCD cameras

Optical filters

Computer programming

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