改进加权FCM用于裂纹蛋2D图像分割的研究  

Improved Weighted FCM in Crack Egg 2D Image Segmentation

作　　者：张莉[1] 郁志宏[1] 

机构地区：[1]内蒙古农业大学机电工程学院,呼和浩特010018

出　　处：《农机化研究》2007年第11期64-66,共3页Journal of Agricultural Mechanization Research

基　　金：内蒙古自然科学基金项目(200408020809)

摘　　要：解决裂纹鸡蛋图像灰度直方图目标与背景区域分布模糊、图像分割效果差的问题。通过将包含空间信息的二维直方图和改进特征加权FCM算法有机结合,迭代寻求最佳聚类有效性函数和加权矩阵,实现鸡蛋图像缺陷分割。同时,对经典FCM和改进特征加权FCM算法的性能进行了分析比较。结果表明:提出的算法更接近于真实聚类中心,目标函数值亦得到改善;二维直方图的改进特征加权模糊聚类算法更好地提取了裂纹鸡蛋图像的细节信息,图像分割效果好。Aim to improve image segmentation effect on crack inspection of eggs. Taking the 2D histogram integrated with spatial information as the sample of improved FCM algorithm with weighted features, iteratively seeking optimal validity function and weighted matrix, crack egg segmentation is achieved. Comparing with the performance of classical FCM, the results show that the algorithm of the improved FCM with weighted features has a better object function and an adjacent clustering data point. The algorithm of improved FCM with weighted features performed in 2D histogram could catch more detail information of image, and the segmentation effect on crack egg image is good.

关 键 词：计算机应用 改进加权FCM 理论研究 2D直方图 图像分割 邻域 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]