Abstract: In industry，speckle noise and the fuzziness of boundaries are usually produced by some disadvantageous factors in image acquired by CCD camera.On this issue，there are many disadvantages in traditional edge detection and edge detection based on fuzzy theory.A multi-level fuzzy enhanced edge detection algorithm is presented.Firstly，the Valley-emphasis algorithm is employed to estimate the optimal threshold parameters.Then，the new convex non-linear membership function based on this threshold is defined to map the fractal gray image into fuzzy feature plane.Finally，fuzzy enhancement with separated regions and smooth processing are given.On this basis，the fuzzy entropy measure is employed to extract edge.Experiments demonstrate the method is effective.The edge detection results can offer an important reference for quality control in industry.

Key words: multi-level fuzzy enhancement, edge detection, fuzzy entropy, industry image

摘要： 在工业上由CCD相机拍摄的图像，因一些不利的因素，会产生斑点噪声且使待检测的目标间强度对比比较明显。对这一问题，目前常用的传统边缘检测和基于模糊理论的边缘检测方法存在着各种缺陷，由此提出了一种多层次模糊增强边缘检测算法。该算法首先使用Valley-emphasis算法来计算阈值参数，根据阈值定义的凸非线性隶属函数对待测灰度图进行模糊特征平面映射，再对模糊域进行平滑处理和模糊增强。在此基础上，提出了基于模糊熵的边缘检测方法。实验结果表明该算法有效，检测结果为工业上质量控制提供了重要依据。

关键词: 多层次模糊增强, 边缘检测, 模糊熵, 工业图像