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Sensors 2011, 11(5), 5337-5359; doi:10.3390/s110505337

A Novel Cloning Template Designing Method by Using an Artificial Bee Colony Algorithm for Edge Detection of CNN Based Imaging Sensors

Electrical and Electronics Engineering, Engineering Faculty, Erciyes University, Turkey
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Author to whom correspondence should be addressed.
Received: 1 April 2011 / Revised: 27 April 2011 / Accepted: 13 May 2011 / Published: 17 May 2011
(This article belongs to the Section Physical Sensors)
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Abstract

Cellular Neural Networks (CNNs) have been widely used recently in applications such as edge detection, noise reduction and object detection, which are among the main computer imaging processes. They can also be realized as hardware based imaging sensors. The fact that hardware CNN models produce robust and effective results has attracted the attention of researchers using these structures within image sensors. Realization of desired CNN behavior such as edge detection can be achieved by correctly setting a cloning template without changing the structure of the CNN. To achieve different behaviors effectively, designing a cloning template is one of the most important research topics in this field. In this study, the edge detecting process that is used as a preliminary process for segmentation, identification and coding applications is conducted by using CNN structures. In order to design the cloning template of goal-oriented CNN architecture, an Artificial Bee Colony (ABC) algorithm which is inspired from the foraging behavior of honeybees is used and the performance analysis of ABC for this application is examined with multiple runs. The CNN template generated by the ABC algorithm is tested by using artificial and real test images. The results are subjectively and quantitatively compared with well-known classical edge detection methods, and other CNN based edge detector cloning templates available in the imaging literature. The results show that the proposed method is more successful than other methods. View Full-Text
Keywords: cellular neural networks; edge detection; artificial bee colony algorithm; real time imaging sensors cellular neural networks; edge detection; artificial bee colony algorithm; real time imaging sensors
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Parmaksızoğlu, S.; Alçı, M. A Novel Cloning Template Designing Method by Using an Artificial Bee Colony Algorithm for Edge Detection of CNN Based Imaging Sensors. Sensors 2011, 11, 5337-5359.

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