摘要
金属表面裂纹是判断金属材料的一个重要指标。由于在图像裂纹处理中有噪声干扰且定位不准确,研究针对图像的锐化算法具有重大意义。本文重点探讨常用的几种锐化算子,分别对金属裂纹图像进行处理,深入分析对比几种锐化算子对图像的处理效果,在大量仿真实验基础上,提出一种有效的混合算法。混合算法减弱了噪声的影响,突出了裂纹边缘特征,取得了良好的实验效果,对后续裂纹识别与分析有十分重要的应用价值。
Cracks on the surface of metal are one of important indexes for judging metal materials.It is very important of researching in image sharpening because of noise jamming and inaccuracy while processing images.In this dissertation,attention is especially focused on several common sharpening operators,respectively on the processing of metal crack images.Several image processing effects of sharpening operators are deeply analyzed and an effective hybrid algorithm is put forward after analyzing a large number of simulation experiments.Not only the influence of the noise jamming is weakened,but also the edge characteristic of image is highlighted.Therefore,the hybrid algorithm shows favorable application value and potential prospect.
出处
《计算机与现代化》
2013年第3期172-174,共3页
Computer and Modernization
关键词
金属裂纹
灰度图像
图像锐化
混合算法
metal crack
gray image
image sharpening
hybrid algorithm
