A constructive genetic algorithm for LBP in face recognition

A. Nazari, S. Shouraki
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引用次数: 6

Abstract

LBP coefficients are essential and determine the priority of gray differences. The objectives of this paper are to reveal this and propose a method for finding an optimal priority through the genetic algorithm. On the other hand, the genetic operators such as initialization and cross-over operators, generate invalid coefficients, defective chromosomes. This paper also recommends a rectifying method for correcting defective chromosomes. Results on the FERET and Extended Yale B datasets indicate that the proposed method has markedly higher recognition rates than LBP.
一种基于LBP的人脸识别建设性遗传算法
LBP系数至关重要,它决定了灰度差的优先级。本文的目的是揭示这一点,并提出了一种通过遗传算法寻找最优优先级的方法。另一方面,初始化和交叉等遗传算子会产生无效系数和缺陷染色体。本文还推荐了一种校正缺陷染色体的校正方法。在FERET和Extended Yale B数据集上的实验结果表明,该方法的识别率明显高于LBP。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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