標題: Automatic classification of block-shaped parts based on their 2D projections
作者: Chuang, JH
Wang, PH
Wu, MC
資訊工程學系
工業工程與管理學系
Department of Computer Science
Department of Industrial Engineering and Management
關鍵字: part classification;block-shaped parts;neural networks
公開日期: 1-Jul-1999
摘要: This paper presents a classification scheme for 3D block-shaped parts. A part is block-shaped if the contours of its orthographic projections are all rectangles, A block-shaped part is classified based on its partitioned view-contours, which are the result of partitioning the contours of its orthographic projections by visible or invisible projected line;segments. The regions and their adjacency in a partitioned view-contour are first converted to a graph, then to a reference tree, and finally to a vector form, with which a back-propagation neural network classifier can be trained and applied. The proposed back-propagation neural network classifier is in a cascaded structure and has advantages that each network can be limited to a small size and trained independently. Based on the classification results on their partitioned view-contours, parts are grouped into families that can be in one of the three levels of similarity. Extensive empirical tests have been performed; the pros and cons of the approach are also investigated. (C) 1999 Elsevier Science Ltd. All rights reserved.
URI: http://hdl.handle.net/11536/31227
ISSN: 0360-8352
期刊: COMPUTERS & INDUSTRIAL ENGINEERING
Volume: 36
Issue: 3
起始頁: 697
結束頁: 718
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