Efficiently Extracting and Classifying Objects for Analyzing Color Documents

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Title:	Efficiently Extracting and Classifying Objects for Analyzing Color Documents
Authors:	Tsai, C. M.;蔡俊明;Lee, H. J.
Contributors:	臺北市立教育大學資訊科學系
Date:	2011
Issue Date:	2017-07-25 09:58:39 (UTC+8)
Abstract:	Conventional objects extraction method are not efficient for color document image with large graphics. For example, the projection profile and connected component based methods scanning the large graphics many times. To display the large graphics are extracted, conventional methods use rectangle to represent it. Thus, scanning into the large graphics is time-consuming. In this paper, a novel system for efficiently analyzing color documents is proposed to solve abovementioned problem. The proposed system includes color transformation, background color determination, objects extraction by top-down method, and objects classification without parameters. The proposed color document analysis system is efficient because it scans only background pixels such that the temporal complexity is O (NB), where NB is the total number of background color pixels. Results of this study demonstrate that this system is more effective and efficient than other methods. Moreover, the proposed algorithm can be run in an embedded environment (such as a mobile device) and processed in real-time system due to its simplicity and efficiency
Relation:	Machine Vision and Applications， Vol. 22， No. 1， pp. 21-37
Appears in Collections:	[Department of Computer Science] Periodical Articles

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