The improved genetic algorithm used to optimize gabor filters for vehicle detection

被引：0
作者：
Jin, Dajiang [1 ]
Long, Lan [1 ]
Zhang, Jiye [1 ]
机构：
[1] Southwest Jiatong Univ, Tract Power State Key Lab, Chengdu 610031, Peoples R China
来源：
PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEMS AND KNOWLEDGE ENGINEERING (ISKE 2007) | 2007年
关键词：
vehicle detection; Gabor filter; genetic algorithm; support vector machine;
D O I：
10.2991/iske.2007.4
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Our focus in this paper is on using the improved Genetic Algorithm (IGA) to optimize Gabor filters for vehicle detection. The Gabor filters parameters are encoded in a chromosome and optimized using genetic operators. Considering the deficiency of the traditional crossover operator at global searching, the partheno-crossover operator, a new crossover operator, is proposed and used to improve GA. The objective is to build the specifically set of filters which are capable of responding stronger to vehicles than to nonvehicles. Compared with using general GA, the Gabor filter optimized by using the IGA allows better correct rate of vehicle detection.
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