文章摘要
融合局部描述子的阈值图像分割算法
An thresholding image segmentation algorithm based on local descriptors fusion
  
DOI:
中文关键词: 图像分割  局部描述子  特征融合  过渡区  局部熵  局部方差
英文关键词: image segmentation  local descriptor  feature fusion  transition region  local entropy  local variance
基金项目:国家自然科学基金资助项目(60975083);肇庆学院青年项目(201321)
作者单位
邹小林 肇庆学院 数学与统计学院,广东 肇庆 526061 
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中文摘要:
      针对基于局部熵的过渡区阈值算法中没有同时考虑局部图像灰度变化的频率和幅度,提出一种融合局部描述子的过渡区阈值算法.提出算法首先采用图像的局部熵和局部方差等局部描述子提取图像的局部特征;其次融合局部图像特征构造特征矩阵,并选取合适的特征阈值提取图像的过渡区;最后根据图像过渡区的灰度均值分割图像.实验结果表明,根据一些图像分割的定量评价标准,提出算法提取过渡区的质量高,分割图像效果好.
英文摘要:
      Because the transition region thresholding algorithm based on local entropy did not simultaneously consider the amplitude and frequency of the local gray varying of the image, a new transition region thresholding algorithm based on a fusion of local descriptors was proposed. Firstly, in the proposed algorithm, local image feature was extracted by using local image descriptors about local entropy and local variance. Secondly, the feature matrix was constructed by the fusion image feature. Thirdly, the transition region was extracted through opposite feature threshold. Finally, the image was segmented by the grayscale mean of transition pixels. The experimental results show the algorithm performs well in transition region extraction and image segmentation.
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