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Sub-pixel extraction of laser stripeand itsapplication in laser plane calibration 被引量:2
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作者 陈平 张志胜 +1 位作者 戴敏 陈恺 《Journal of Southeast University(English Edition)》 EI CAS 2015年第1期107-112,共6页
For calibrating the laser plane to implement 3D shape measurement, an algorithm for extracting the laser stripe with sub-pixel accuracy is proposed. The proposed algorithm mainly consists of two stages: two-side edge... For calibrating the laser plane to implement 3D shape measurement, an algorithm for extracting the laser stripe with sub-pixel accuracy is proposed. The proposed algorithm mainly consists of two stages: two-side edge detection and center line extraction. First, the two-side edge of laser stripe is detected using the principal component angle-based progressive probabilistic Hough transform and its width is calculated through the distance between these two edges. Secondly, the center line of laser strip is extracted with 2D Taylor expansion at a sub-pixel level and the laser plane is calibrated with the 3D reconstructed coordinates from the extracted 2D sub-pixel ones. Experimental results demonstrate that the proposed method can not only extract the laser stripe at a high speed, nearly average 78 ms/frame, but also calibrate the coplanar laser stripes at a low error, limited to 0.3 mm. The proposed algorithm can satisfy the system requirement of two-side edge detection and center line extraction, and rapid speed, high precision, as well as strong anti-jamming. 展开更多
关键词 sub-pixel extraction center line extraction laser plane calibration progressive probabilistic Hough transform (PPHT) principal component pc angle 2D Taylor expan- sion
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PRINCIPAL COMPONENT ANALYSIS IN APPLICATION TO OBJECT ORIENTATION
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作者 WEI Yi S.MarshallWEI Yi,Ph.D.Candidate,University of Strathclyde,UKKEY WORDS principal component analysis(PCA) principal component(PC) +2 位作者 observed samples eigenvector eigenvalue 《Geo-Spatial Information Science》 2000年第3期76-78,共3页
This paper proposes a new method based on principal component analysis to find the direction of an object in any pose.Experiments show that this method is fast,can be applied to objects with any pixel distribution and... This paper proposes a new method based on principal component analysis to find the direction of an object in any pose.Experiments show that this method is fast,can be applied to objects with any pixel distribution and keep the original properties of objects invariant.It is a new application of PCA in image analysis. 展开更多
关键词 principal COMPONENT analysis(pcA) principal component(pc) OBSERVED SAMPLES EIGENVECTOR EIGENVALUE
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