NDLI: A New Scan-Line Algorithm Using Clustering Approach

Content Provider	IEEE Xplore Digital Library
Author	Xiaoguang Tian Ma, Y. Xiaorong Hou
Copyright Year	2009
Abstract	Correct recognition of the lines is essential for technical drawing understanding. Automation solution is quite difficult due to the limitations of machine vision algorithm. In order to promote development of better technology, according to the fast and high-quality clustering algorithm Particle Swarm Optimization (PSO), a new fast and high-quality line clustering algorithm present in this paper, that consisting of one scan-line connected components processing are clustered and an appropriate measure to recognize the pattern of every line including the dash-line in the drawing paper. The underlying mechanisms are excluding isolated components, a sequential stepwise recovery of components that meet certain continuity conditions and the results presented the node-tree structure that can enhance efficiency of computer. The performance of the algorithm is better in our experiment
Starting Page	84
Ending Page	89
File Size	471706
Page Count	6
File Format	PDF
ISBN	9780769537450
DOI	10.1109/HIS.2009.129
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-08-12
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Automation clustering algorithm recognition of the lines Educational institutions Data mining Character recognition Appropriate technology Technical drawing Particle swarm optimization recovery of the lines Machine vision Clustering algorithms particle swarm optimization (PSO) Hybrid intelligent systems scan-line algorithm
Content Type	Text
Resource Type	Article

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