边界局部搜索算法与应用  

Local border search algorithm and its application

作　　者：吴贵芳[1] 徐科[1] 徐金梧[1] 

机构地区：[1]北京科技大学机械工程学院,北京100083

出　　处：《计算机应用》2005年第2期326-328,共3页journal of Computer Applications

基　　金：国家自然科学基金资助项目(50074010);国家 863计划项目(2003AA331080)

摘　　要：提出一种快速的边部检测算法,即边界局部搜索算法,并应用于冷轧带钢表面缺陷在线检测系统.它采用一种局部搜索的思想,在前一次搜索的基础上准确定位钢板边部,大大提高了算法的实现速度.对现场图像数据测试表明,边界局部搜索算法比传统的灰度梯度阈值算法的速度快20～200倍左右,并且检测的效果得到有效的提高.这种算法还可以用于其他图像边界的搜索.A fast border-detection algorithm named local border search algorithm was presented here, and applied to an on-line surface inspection system for cold rolled strips. Based on the last search result, a local search was used to position the cold rolled strip border and increased the algorithms speed greatly. Test with images collected from real world data shows that local border search algorithm is about 20 to 200 times faster than the traditional gray level gradient threshold algorithm, and can detect borders more accurately. The algorithm can also be used in the search of other image border.

关 键 词：边界局部搜索 图像处理 冷轧带钢 表面检测 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]