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基于二维阈值向量的木材表面缺陷分割方法
引用本文:白雪冰,王科俊,邹丽晖. 基于二维阈值向量的木材表面缺陷分割方法[J]. 东北林业大学学报, 2008, 36(9)
作者姓名:白雪冰  王科俊  邹丽晖
作者单位:哈尔滨工程大学,哈尔滨,150001;北京理工大学
基金项目:黑龙江省博士后科研启动基金 
摘    要:根据木材表面缺陷图像的自身特点,提出了基于灰度—梯度二维阈值向量的缺陷区域分割方法。该方法以灰度—梯度共生矩阵为模型,通过计算基于灰度—梯度共生矩阵的二维熵并使边缘区域的熵最大化来选择二维阈值向量。该方法不仅利用了图像的灰度信息,也利用了图像的梯度信息。采用形态学运算对分割后的二值图像进行分割后处理,试验表明,分割效果良好。

关 键 词:木材表面缺陷  图像分割  灰度-梯度共生矩阵  最大熵  形态学

An Approach to Segmentation of Wood Surface Defects Based on 2D Threshold Vectors
Bai Xuebing,Wang Kejun. An Approach to Segmentation of Wood Surface Defects Based on 2D Threshold Vectors[J]. Journal of Northeast Forestry University, 2008, 36(9)
Authors:Bai Xuebing  Wang Kejun
Abstract:According to the characteristics of wood surface defects, an approach to the segmentation of defect region based on two-dimensional gray level-gradient threshold vector is presented. It takes gray level-gradient co-occurrence matrix as a model and uses maximum entropy theory, namely, the approach evaluates two-dimensional entropies based on gray level-gradient co-occurrence matrix, and 2D threshold vector which maximizes the entropies of edge region is selected. This method attempts to utilize the information both of gray level and gradient in an image. And it carries on post-processing to the segmented binary images by morphology operation. The segmentation experiment shows good results.
Keywords:Wood surface defects  Image segmentation  Gray level-gradient co-occurrence matrix  Maximum entropy  Morphology
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