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

Joint Authors

Gunes, Mahit
Badem, Hasan

Source

Journal of Sensors

Issue

Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-11, 11 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2016-10-05

Country of Publication

Egypt

No. of Pages

11

Main Subjects

Civil Engineering

Abstract EN

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.

American Psychological Association (APA)

Gunes, Mahit& Badem, Hasan. 2016. Detecting Direction of Pepper Stem by Using CUDA-Based Accelerated Hybrid Intuitionistic Fuzzy Edge Detection and ANN. Journal of Sensors،Vol. 2016, no. 2016, pp.1-11.
https://search.emarefa.net/detail/BIM-1110450

Modern Language Association (MLA)

Gunes, Mahit& Badem, Hasan. Detecting Direction of Pepper Stem by Using CUDA-Based Accelerated Hybrid Intuitionistic Fuzzy Edge Detection and ANN. Journal of Sensors No. 2016 (2016), pp.1-11.
https://search.emarefa.net/detail/BIM-1110450

American Medical Association (AMA)

Gunes, Mahit& Badem, Hasan. Detecting Direction of Pepper Stem by Using CUDA-Based Accelerated Hybrid Intuitionistic Fuzzy Edge Detection and ANN. Journal of Sensors. 2016. Vol. 2016, no. 2016, pp.1-11.
https://search.emarefa.net/detail/BIM-1110450

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1110450