基于云空间和模糊熵的边缘检测算法

Fuzzy Edge Detection Algorithm of Image Based on Cloud Space and Fuzzy Entropy

基于模糊集理论及云理论,提出了对象云的图像模糊边缘检测方法(OCFD)。算法充分考虑图像的模糊性和随机性,建立起图像空间与云空间的映射模型,生成模糊对象云和边界云,完成图像空间到云空间的映射。在云空间中实现逻辑云运算的边界云提取,提出并实现了基于边界云的过渡区定义及其提取算法。最后利用最大模糊熵在过渡区内实现检测边缘。实验证明,OCFD算法在检测性能方面优于模糊Sobel,Pal.King等算法,为图像的模糊理解和分析提供了一种新的思路,同时也丰富和拓展了云理论。

Based on fuzzy set theory and cloud theory, fuzzy edge detection algorithm based on object cloud, OCFD was proposed. Considering the fuzzy and random characteristics of image, OCFD constructed the mapping model between ima- ge space and cloud space by the representation methods of uncertain object cloud in image. According to the mapping model, object cloud and edge cloud could be generated. Mapping from image space to cloud space could be accomplished based on object cloud and edge cloud. By logical cloud calculating in cloud space, the algorithm of transition region de- tection was proposed. Based on maximum fuzzy entropy principle, edge detection in transition region could be accom- plished. Experiments demonstrate that OCFD exhibits a considerable improvement in performance compared with both Fuzzy C-mean and Pal. King. The algorithm proposes a new idea for image comprehending and analyzing. It enriches and extends the cloud theory.