Edge Detection for Range Images Based On Genetic BP Neural Networks
In this paper, a kind of edge detection method based on image features and genetic algorithms neural network for range images is proposed. Fully considering the essential difference between an edge point and a noise point, some characteristic parameters are extracted from range maps as the input nodes of the network in the algorithm. Firstly, genetic algorithms will be used to train the neural networks, and then the trained neural network model can solve the edge detection problem. The experimental results show that this method can be much faster and more accurate detection results than the classical differential algorithm, and has better anti-noise performance.
range image neural networks genetic algorithms
Jianying Fan Ying Du Yang Zhou Yang Wang
Department of Measurement-Control Technology & Instrument Harbin University of Science & Technology Harbin, Heilongjiang Province, China
国际会议
2008 Sino-European Workshop on Intelligent Robots and Systems(SEIROS08)(第一届中欧智能系统及机器人国际学术研讨会)
重庆
英文
1-4
2008-12-11（万方平台首次上网日期，不代表论文的发表时间）