首页> 外文会议>Advances in Neural Networks - ISNN 2007 pt.2; Lecture Notes in Computer Science; 4492 >Edge Detection Combined Entropy Threshold and Self-Organizing Map (SOM)
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Edge Detection Combined Entropy Threshold and Self-Organizing Map (SOM)

机译:边缘检测结合熵阈值和自组织映射(SOM)

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An edge detection method by combining image entropy and Self -Organizing Map (SOM) is proposed in this paper. First, according to information theory image entropy is used to curve up the smooth region and the region of gray level abruptly changed. Then we transform the gray level image to ideal binary pattern of pixels. We define six classes' edge and six edge prototype vectors. These edge prototype vectors are fed into input layer of the Self-Organizing Map (SOM). Classifying the type of edge through this network, the edge image is obtained. At last, the speckle edges are discarded from the edge image. Experimental results show that it gained better edge image compared with Canny edge detection method.
机译:提出了一种结合图像熵和自组织图(SOM)的边缘检测方法。首先,根据信息论,图像熵被用于弯曲平滑区域,并且灰度区域突然改变。然后,我们将灰度图像转换为理想的像素二进制图案。我们定义了六个类的边缘和六个边缘原型向量。这些边缘原型向量被馈送到自组织映射(SOM)的输入层。通过该网络分类边缘的类型,获得边缘图像。最后,从边缘图像中去除斑点边缘。实验结果表明,与Canny边缘检测方法相比,它获得了更好的边缘图像。

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