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Micro-Object Detection by Dynamic ROI Combined with Pyramid Template Matching
Zhijie Nan; Qingsong Xu
2018
Conference Name2018 37th Chinese Control Conference (CCC)
Source Publication2018 37th Chinese Control Conference (CCC)
Conference Date25-27 July 2018
Conference PlaceWuhan, China
Abstract

This paper introduces a new detection method of objects in micro-scale based on dynamic region of interest (ROI) method combined with pyramid template matching (PTM) approach. The dynamic ROI method works based on the position predicting, which is provided by the Kalman filter (KF). Rather than searching the entire image, the detection ROI is located at a limited region. Experimental results show that the detected positions match well with the real motion path. Moreover, the dynamic ROI method reduces the computation time by 30% as compared with the PTM algorithm

KeywordMachine Vision Kalman Filter Dynamic Roi Intelligent Robot
DOIhttp://doi.org/10.23919/ChiCC.2018.8484199
Language英语
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Document TypeConference paper
CollectionFaculty of Science and Technology
DEPARTMENT OF ELECTROMECHANICAL ENGINEERING
AffiliationDepartment of Electromechanical Engineering, Faculty of Science and Technology, University of Macau, Macau, China
First Author AffilicationFaculty of Science and Technology
Recommended Citation
GB/T 7714
Zhijie Nan,Qingsong Xu. Micro-Object Detection by Dynamic ROI Combined with Pyramid Template Matching[C],2018.
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