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Edge detection of range images using genetic neural networks
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作者 FAN Jian-ying DU Ying ZHOU Yang WANG Yang 《重庆邮电大学学报(自然科学版)》 北大核心 2009年第2期272-275,共4页
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 ge... 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. 展开更多
关键词 遗传神经网络 基于图像 检测范围 遗传算法 边缘检测方法 神经网络训练 神经网络算法 参数提取
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