TWO-STAGE OCCLUDED OBJECT RECOGNITION METHOD FOR MICROASSEMBLY  

作　　者：WANG Huaming ZHU Jianying 

机构地区：[1]Electrical Engineering,Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China

出　　处：《Chinese Journal of Mechanical Engineering》2007年第1期115-119,共5页中国机械工程学报（英文版）

基　　金：This project is supported by National Natural Science Foundation of China (No. 50275078)

摘　　要：A two-stage object recognition algorithm with the presence of occlusion is presented for microassembly. Coarse localization determines whether template is in image or not and approximately where it is, and fine localization gives its accurate position. In coarse localization, local feature, which is invariant to translation, rotation and occlusion, is used to form signatures. By comparing signature of template with that of image, approximate transformation parameter from template to image is obtained, which is used as initial parameter value for fine localization. An objective function, which is a function of transformation parameter, is constructed in fine localization and minimized to realize sub-pixel localization accuracy. The occluded pixels are not taken into account in objective function, so the localization accuracy will not be influenced by the occlusion.A two-stage object recognition algorithm with the presence of occlusion is presented for microassembly. Coarse localization determines whether template is in image or not and approximately where it is, and fine localization gives its accurate position. In coarse localization, local feature, which is invariant to translation, rotation and occlusion, is used to form signatures. By comparing signature of template with that of image, approximate transformation parameter from template to image is obtained, which is used as initial parameter value for fine localization. An objective function, which is a function of transformation parameter, is constructed in fine localization and minimized to realize sub-pixel localization accuracy. The occluded pixels are not taken into account in objective function, so the localization accuracy will not be influenced by the occlusion.

关 键 词：Object recogntion Local feature Sub-pixel Objective function 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]