A NOVEL HYBRID EDGE DETECTION TECHNIQUE: ABC-FA

Year 2017, Issue: 1, 193 - 200, 09.11.2017

Elif Deniz Yelmenoglu Numan Celebi Tugrul Tasci

https://izlik.org/JA54LL74LE

Abstract

Image processing is a vast
research field with diversified set of practices utilized in so many
application areas such as military, security, medical imaging, machine learning
and computer vision based on extracted useful information from any kind of image
data. Edges within images are undoubtedly accepted as one of the most
significant features providing substantial practical information for various
applications working on top of miscellaneous optimization algorithms to achieve
better results. Artificial Bee Colony and Firefly algorithms are recently
developed optimization algorithms and are used to obtain better results for
various problems. In this study, a novel hybrid optimization technique is
proposed by combining those algorithms aiming better quality in edge detection
on grayscale images. The performance of the
proposed algorithm is compared with individual performances of
Artificial Bee Colony algorithm and the fundamental edge detection methods. The results are demonstrated that the
proposed method is encouraging and also produces meaningful results for similar
applications.

Keywords

Image processing , edge detection , meta-heuristic , artificial bee colony (abc) , firefly (fa)

References

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