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Proceedings Paper

Optimization of focus measure using genetic algorithm
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Paper 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.

Paper Details

Date Published: 15 September 2008
PDF: 8 pages
Proc. SPIE 7073, Applications of Digital Image Processing XXXI, 70731T (15 September 2008); doi: 10.1117/12.798209
Show Author Affiliations
Ik-Hyun Lee, Gwangju Institute of Science and Technology (Korea, Republic of)
Muhammad Tariq Mahmood, Gwangju Institute of Science and Technology (Korea, Republic of)
Tae-Sun Choi, Gwangju Institute of Science and Technology (Korea, Republic of)


Published in SPIE Proceedings Vol. 7073:
Applications of Digital Image Processing XXXI
Andrew G. Tescher, Editor(s)

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