固体推进剂药柱图像的自适应阈值分割方法  

Auto-adaptive threshold segmentation algorithm for image of solid propellants grains

作　　者：曾接贤[1] 龚勇[2] 

机构地区：[1]南昌航空大学计算机学院,南昌330063 [2]南昌航空大学无损检测技术教育部重点实验室,南昌330063

出　　处：《计算机工程与应用》2008年第28期98-100,132,共4页Computer Engineering and Applications

基　　金：国家自然科学基金No.60675022;江西省自然科学基金No.0311019;江西省教育厅科技计划项目~~

摘　　要：以固体推进剂药柱内窥镜图像表面缺陷的自动检测为例,在分析了此类图像特征的基础上,提出了一种利用梯度直方图信息的图像自适应阈值分割算法。通过实例,与原自适应直方图阈值分割算法和固定阈值分割算法相比较,结果表明:该算法采用可动态调整的形态学梯度算子计算梯度直方图,充分利用了图像的边缘信息和缺陷内部灰度分布不均匀的特性,算法简单,适应性广,具有实时准确分割图像的特点。Taking for example auto-detection of surface defects of Endoscopic Image of Solid Propellants Grains,this paper analyses the characters of product surface images.An adaptive image segmentation algorithm based on information of gradient- histogram is presented to improve detection precision of product surface defects and reduce the cost.In the end,the algorithm is compared with auto-adaptive histogram threshold segmentation algorithm and fixed threshold segmentation algorithm.The results indicate that the algorithm adopts dynamic adjustable morphologic operator to calculate gradient histogram,has wide adaptability by making the best of the characters of edge information and uneven gray level distribution in defects,and has the ability of segmenting real-time image exactly.

关 键 词：形态学梯度算子 梯度直方图 图像分割 表面缺陷 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]