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Advances in Control and Communication pp 681–688Cite as

Extracting Image Semantic Object Based on Artificial Bee Colony Algorithm

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Part of the Lecture Notes in Electrical Engineering book series (LNEE,volume 137)

Abstract

In this paper, an efficient approach for extracting semantic object using artificial bee colonyalgorithm (ABCA) has been proposed. First, we reduce speckle noise in the image. Then fitness function of ABC algorithm is constructed, and image pixels are classified into different regions. Further semantic objects are extracted in terms of color information. The simulation results show that the color clustering via bee colony algorithm gives superior results in enhancing cluster compactness.

Keywords

  • artificial bee colony algorithm
  • image semantic
  • image segmentation

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Author information

Authors and Affiliations

  1. School of Electronic and Information Engineering, South China University of Technology, Guangzhou, 510641, China

    Xiao Yong-hao, Chen Yong-chang & Yu Wei-yu

  2. Provincial Key Laboratory for Computer Information Processing Technology, Soochow University, Suzhou, China

    Xiao Yong-hao & Yu Wei-yu

  3. School of Electrical and Electronic Engineering, Nanyang Technological University, Nanyang, 639798, Singapore

    Tian Jing

Authors
  1. Xiao Yong-hao
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  2. Chen Yong-chang
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  3. Yu Wei-yu
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  4. Tian Jing
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Editor information

Editors and Affiliations

  1. Shenzhen University, Guangdong, 518060, China, People's Republic

    Dehuai Zeng

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Yong-hao, X., Yong-chang, C., Wei-yu, Y., Jing, T. (2012). Extracting Image Semantic Object Based on Artificial Bee Colony Algorithm. In: Zeng, D. (eds) Advances in Control and Communication. Lecture Notes in Electrical Engineering, vol 137. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-26007-0_84

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  • DOI: https://doi.org/10.1007/978-3-642-26007-0_84

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