Combining Block and Corner Features for Content-Based Trademark Retrieval  

作　　者：HONG Zhiling JIANG Qingshan WU Meihong 

机构地区：[1]School of Information Science and Technology, Xiamen University, Xiamen 361005, Fujian, China [2]School of Software, Xiamen University, Xiamen 361005, Fujian, China

出　　处：《Wuhan University Journal of Natural Sciences》2007年第5期907-911,共5页武汉大学学报（自然科学英文版）

基　　金：Supported by the National High Technology Research and Development Program of China(863 Program) (2006AA01Z129);the 985-2 Project (0000-X07204) of Xiamen University

摘　　要：In order to retrieve a similarly look trademark from a large trademark database, an automatic content based trademark retrieval method using block hit statistic and comer Delaunay Triangulation features was proposed. The block features are derived from the hit statistic on a series of concentric ellipse. The comers are detected based on an enhanced SUSAN （Smallest Univalue Segment Assimilating Nucleus） algorithm and the Delaunay Triangulation of comer points are used as the comer features. Experiments have been conducted on the MPEG-7 Core Experiment CE-Shape-1 database of 1 400 images and a trademark database of 2 000 images. The retrieval results are very encouraging.In order to retrieve a similarly look trademark from a large trademark database, an automatic content based trademark retrieval method using block hit statistic and comer Delaunay Triangulation features was proposed. The block features are derived from the hit statistic on a series of concentric ellipse. The comers are detected based on an enhanced SUSAN （Smallest Univalue Segment Assimilating Nucleus） algorithm and the Delaunay Triangulation of comer points are used as the comer features. Experiments have been conducted on the MPEG-7 Core Experiment CE-Shape-1 database of 1 400 images and a trademark database of 2 000 images. The retrieval results are very encouraging.

关 键 词：content-based image retrieval TRADEMARK concentric ellipse enhanced SUSAN 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]