重庆邮电大学学报（自然科学版）2009，Vol.21Issue(2)：272-275,4.
Edge detection of range images using genetic neural networks
Edge detection of range images using genetic neural networks
FAN Jian-ying 1DU Ying 1ZHOU Yang 1WANG Yang1
作者信息
- 1. Department of Measurement-Control Technology & Instrument,Harbin University of Science & Technology,Harbin 150080, P. R. China
- 折叠
摘要
Abstract
Due to the complexity and asymmetrical illumination, the images of object are difficult to be effectively segmented by some routine method. In this paper, a kind of edge detection method based on image features and genetic algorithms neural network for range images was proposed. Fully considering the essential difference between an edge point and a noise point, some characteristic parameters were extracted from range maps as the input nodes of the network in the algorithm. Firstly, a genetic neural network was designed and implemented. The neural network is trained by genetic algorithm, and then genetic neural network algorithm is combined with the virtue of global optimization of genetic algorithm and the virtue of parallel computation of neural network, so that this algorithm is of good global property. The experimental results show that this method can get much faster and more accurate detection results than the classical differential algorithm, and has better anti-noise performance.关键词
range image/neural networks/genetic algorithmsKey words
range image/neural networks/genetic algorithms分类
信息技术与安全科学引用本文复制引用
FAN Jian-ying,DU Ying,ZHOU Yang,WANG Yang..Edge detection of range images using genetic neural networks[J].重庆邮电大学学报（自然科学版）,2009,21(2):272-275,4.
