TWO-STAGE OCCLUDED OBJECT RECOGNITION METHOD FOR MICROASSEMBLY

被引:0
|
作者
WANG Huaming ZHU Jianying School of Mechanical and Electrical Engineering
机构
基金
中国国家自然科学基金;
关键词
Object recognition Local feature Sub-pixel Objective function;
D O I
暂无
中图分类号
TG95 [机器装配、机器安装法];
学科分类号
080201 ;
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.
引用
收藏
页码:115 / 119
页数:5
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