https://scholars.lib.ntu.edu.tw/handle/123456789/342809
標題: | Recognition of 3-D Object Using Modified 3-D General Hough Transformation | 作者: | REN-CHYUAN LUO W. S. Yang Y. H. Kim |
關鍵字: | Accumulator array; Binary search tree; Data base; Gaussian curvature; Hough transformation; Mean curvature; Normal; Recognition; Reference point; Three dimension | 公開日期: | 一月-1988 | 起(迄)頁: | 64-69 | 來源出版物: | IEEE International Conference on Industrial Electronics | 摘要: | The objective of this paper is to develop an innovative 3-D objects recognition algorithm which solves correspondence problem and reduces computational cost for recognition. Correspondency between features of unknown object and its model and complicated computation for recognition seem to be a bottleneck of current 3-D object recognition. Three-dimensional generalized Hough transformation is introduced which can be applied to general 3-D objects, and reduces both the computation time and data base memory requirements. Data base is constructed in off-line fashion based on the view-point independent characteristics from the known 3-D objects using generalized 3-D Hough transformation. In the recognition process, view-. point independent characteristics from unknown objects are obtained and used as a key for searching the data base for the best candidate. To test the algorithm, various types of objects are investigated by use of 3-D range data. © 1988 IEEE. |
URI: | http://scholars.lib.ntu.edu.tw/handle/123456789/342809 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85069175934&doi=10.1109%2fIECON.1988.660418&partnerID=40&md5=18c520001e60c1e296812144896d1c31 |
DOI: | 10.1109/IECON.1988.660418 | SDG/關鍵字: | Agricultural robots; Binary trees; Computer vision; Industrial electronics; Object recognition; Robotics; Trees (mathematics); Accumulator array; Binary search trees; Gaussian curvatures; Hough Transformation; Mean curvature; Normal; Recognition; Reference points; Three dimensions; Metadata |
顯示於: | 電機工程學系 |
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