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TWO-STAGE OCCLUDED OBJECT RECOGNITION METHOD FOR MICROASSEMBLY

TWO-STAGE OCCLUDED OBJECT RECOGNITION METHOD FOR MICROASSEMBLY
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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.
机构地区 Electrical Engineering
出处 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 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)
关键词 Object recogntion Local feature Sub-pixel Objective function Object recogntion Local feature Sub-pixel Objective function
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参考文献11

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