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Efficiently extracting and classifying objects for analyzing color documents

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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 above mentioned 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.

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Authors and Affiliations

  1. Department of Computer Science, Taipei Municipal University of Education, No. 1, Ai-Kuo W. Road, Taipei, 100, Taiwan

    Chun-Ming Tsai

  2. Department of Medical Informatics, Tzu Chi University, Hualien, 970, Taiwan

    Hsi-Jian Lee

Authors
  1. Chun-Ming Tsai
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  2. Hsi-Jian Lee
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Correspondence to Chun-Ming Tsai.

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Tsai, CM., Lee, HJ. Efficiently extracting and classifying objects for analyzing color documents. Machine Vision and Applications 22, 1–19 (2011). https://doi.org/10.1007/s00138-009-0215-x

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  • DOI: https://doi.org/10.1007/s00138-009-0215-x

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