An Optimal Edge Detection Using Gravitational Search Algorithm

Abstract—Edge detection is a fundamental tool used in most image processing applications to obtain information from the image as a precursor step to feature extraction and object segmentation. Gravitational search algorithm (GSA) is a new population-based search algorithm inspired by Newtonian gravity. Algorithm uses the theory of Newtonian gravity and its searcher agents are the collection of masses. Masses attract each other by way of gravity force, and this force causes a global movement of all objects towards the objects with heavier masses. In the proposed approach the edges are detected by the local variation in intensity values and the movement of agents is computed using gravitational search algorithm. The proposed approach is able to detect the edge pixel in an image up to a certain extent. The technique can be further extended for finding more edge pixels by modifying the gravitational search algorithm.

Index Terms—Gravitational search algorithm, edge, intensity, Fitness function, optimization.

Om Prakash Verma is with the Department of Information Technology, Delhi Technological University (formally DCE), New Delhi, DL 110042, India (e-mail:opverma.dce@gmail.com).
Rishabh Sharma is with the Ericsson India Global Services Pvt. Ltd, Noida, India (e-mail:rishabhs.32@gmail.com).
Manoj Kumar is with the Department of Computer Engineering, Delhi Technological University (formally DCE), New Delhi, DL 110042, India (e-mail:mkg1109@rediffmail.com).
Neetu Agrawal is with the Department of Electronics and Communication, Ambedker Institute of Technology, New Delhi, DL 110031, India (e-mail:neetu24@gmail.com).

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Cite: Om Prakash Verma, Rishabh Sharma, Manoj Kumar, and Neetu Agrawal, "An Optimal Edge Detection Using Gravitational Search Algorithm," Lecture Notes on Software Engineering vol. 1, no. 2, pp. 148-152, 2013.