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An Optimal Edge Detection Using Modified Artificial Bee Colony Algorithm

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Proceedings of the National Academy of Sciences, India Section A: Physical Sciences Aims and scope Submit manuscript

Abstract

This paper proposes a new approach for edge detection using a combination of artificial bee colony (ABC) algorithm and an improved derivative technique. ABC algorithm simulates the foraging behavior of a honey bee swarm. The proposed approach find the edge pixels by an improved derivative technique to compute fitness function, and then applying ABC algorithm determine the most fit pixels to be considered as the edge pixels. Qualitative and quantitative analysis of the proposed approach and its comparison with other standard edge detection methods are presented. Shannon’s entropy function and Pratt’s figure of merit are used for quantitative analysis. The effect of variation of parameters on performance of the proposed approach is discussed. Experimental results show that proposed method outperformed most of existing techniques.

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Authors and Affiliations

  1. Department of Information Technology, Delhi Technological University, Delhi, India

    Om Prakash Verma

  2. Department of Electronics Engineering, Ambedkar Institute of Technology, Geeta Colony, Delhi, India

    Neetu Agrawal

  3. IBM India Pvt. Ltd., Ahmedabad, India

    Siddharth Sharma

Authors
  1. Om Prakash Verma
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  2. Neetu Agrawal
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  3. Siddharth Sharma
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Corresponding author

Correspondence to Neetu Agrawal.

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Verma, O.P., Agrawal, N. & Sharma, S. An Optimal Edge Detection Using Modified Artificial Bee Colony Algorithm. Proc. Natl. Acad. Sci., India, Sect. A Phys. Sci. 86, 157–168 (2016). https://doi.org/10.1007/s40010-015-0256-7

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  • DOI: https://doi.org/10.1007/s40010-015-0256-7

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