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Journal of Sensors
Volume 2016 (2016), Article ID 4052101, 11 pages
Research Article

Detecting Direction of Pepper Stem by Using CUDA-Based Accelerated Hybrid Intuitionistic Fuzzy Edge Detection and ANN

1Department of Electrical and Electronical Engineering, Kahramanmaras Sutcu Imam University, Kahramanmaras, Turkey
2Department of Computer Engineering, Erciyes University, Kayseri, Turkey

Received 1 June 2016; Accepted 8 September 2016

Academic Editor: Stephane Evoy

Copyright © 2016 Mahit Gunes and Hasan Badem. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


In recent years, computer vision systems have been used in almost every field of industry. In this study, image processing algorithm has been developed by using CUDA (GPU) which is 79 times faster than CPU. We had used this accelerated algorithm in destemming process of pepper. 65 percent of total national production of pepper is produced in our cities, Kahramanmaras and Gaziantep in Turkey. Firstly, hybrid intuitionistic fuzzy algorithm edge detection has been used for preprocessing of original image and Otsu method has been used for determining automatic threshold in this algorithm. Then the multilayer perceptron artificial neural network has been used for the classification of patterns in processed images. Result of ANN test for detection direction of pepper has shown high accuracy performance in CPU-based implementation and in GPU-based implementation.