基于网格IC图象的多模板快速匹配算法  被引量:2

A Fast Multiple Template Matching Algorithm Based on Grid Structure IC Images

在线阅读下载全文

作  者:韦燕凤[1] 彭思龙[1] 

机构地区:[1]中国科学院自动化研究所集成电路工程中心,北京100080

出  处:《中国图象图形学报(A辑)》2003年第2期193-197,共5页Journal of Image and Graphics

摘  要:为了加快 IC图象中多个相似单元模板的匹配与定位 ,提出了一种基于网格 IC图象的多模板快速匹配算法 .该算法首先抽取网格图象和模板的二值拓扑结构 ,以构成图象和模板的粗分辨率表示 ;然后 ,在拓扑结构表示上通过综合来构造多模板的二叉树模型 ;接着 ,在二值拓扑结构表示上运用树模型进行搜索 ,在搜索过程中应用二叉决策树识别多个模板 ;最后 ,将粗匹配得到的目标 ,在原图象对应位置的小邻域内进行二次匹配 ,以确定模板和对应实例的位置 .应用此算法对 IC图象库进行测试 ,结果表明 ,所提出的多模板二叉决策树搜索算法与逐个模板匹配的方法相比 。In order to accelerate the matching and locating speed of multiple circuit cell templates which are all similar to each other in integrate circuit (IC) micro images, a fast multiple template matching algorithm based on the uniform grid structure of IC image is proposed. First, the binary topological structure of the original image and multiple templates is decimated base on their uniform grid structure, and the decimated binary topological structure is the coarse resolution representation of the original image and templates. Second, a synthesis strategy is designed to construct a binary tree model of multiple templates' topological structure. Third, the tree model is applied to search in the coarse resolution images, and the binary tree decision is used to recognize multiple templates during the search. Finally, the matched targets in the coarse resolution image are guided to a small region of the original image. The corresponding original template is matched on that region for the true target and exact position. This algorithm is tested with IC micro images database. It shows that the proposed multiple templates binary tree model and the decimation of topological structure can highly increase the matching speed and the efficiency of the cells matching and location system. Compare to searching multiple templates sequentially on the original images, the speed up factor of binary tree model is very high.

关 键 词:计算机图象处理 多模板匹配 拓扑结构抽取 二叉决策树 网格IC图象 

分 类 号:TP391.41[自动化与计算机技术—计算机应用技术]

 

参考文献:

正在载入数据...

 

二级参考文献:

正在载入数据...

 

耦合文献:

正在载入数据...

 

引证文献:

正在载入数据...

 

二级引证文献:

正在载入数据...

 

同被引文献:

正在载入数据...

 

相关期刊文献:

正在载入数据...

相关的主题
相关的作者对象
相关的机构对象