Year 2019, Volume 22 , Issue , Pages 95 - 108 2019-11-29

Pamuktaki Yabancı Elyafların GPU ile Hızlandırılmış Sezgisel Bulanık Mantık ve Otsu Algoritmaları ile Tesbiti
GPU Accelerated Intuitionistic Fuzzy and Otsu Algorithms for Foreign Leaf Detection in Cotton

Eyüp Yalçın [1] , Mahit GÜNEŞ [2]


Tekstil, pamuk ve çırçır fabrikalarında kullanılan veya dışarıdan gelen yün ve pamuk ham maddelerinin üretimi ve şekillendirilmesinde ortaya çıkan yabancı maddeler, elde edilen kumaş veya ipliğin kalitesini önemli ölçüde azaltır. Günümüzde tekstil sektöründeki yabancı maddeleri ayırmak için farklı yöntemler kullanılmaktadır, ancak  bu yöntemlerin çoğu hız ve kalite açısından verimli değildir. Bilgisayarlı görme sistemleri, diğer alanlarda olduğu gibi tekstil alanında da hayati bir rol oynamaktadır. Bu çalışmada, kameradan elde edilen görüntülerdeki yabancı maddeleri tanımlamak için Sezgisel Bulanık Mantık kullanılmıştır. CPU tabanlı uygulamalar ilgili algoritmanın yapısı gereği hız problemlerine yol açmaktadır. Bu hız problemini gidermek için ise GPU teknolojisi kullanılmıştır. Otsu algoritması kullanarak Sezgisel bulanık mantık algoritmasıyla elde edilen görüntüler için dinamik bir eşik değeri hesaplanmıştır. Bu sayede, kameradan elde edilen her karenin eşik değeri gerçek zamanlı olarak hesaplanmış ve görüntüye aynı anda uygulanmıştır. Bu algoritmalar, NVIDIA GTX 480 GPU destekli ekran kartı kullanılarak maksimum 262 kez hızlandırılmıştır.

The foreign substances, arising during the production and shaping of wool and cotton raw materials that are used in textile and cotton gin factories or coming from the outside, decrease considerably the quality of the obtained fabric or yarn. Nowadays, a different methods are used to separate foreign substances in the textile sector, most of these methods are not efficient in terms of speed and quality. Computerized vision systems play a vital role in the field of textiles as in other fields. In this study, Intuitionistic Fuzzy Algorithm is used to define the foreign substances in the images that obtained from a camera. CPU (Central Processing Unit) based applications have speed problems due to the structure of the algorithm. For this reason, GPU (Graphics Processing Unit) technology was used to overcome the speed problem. The otsu algorithm generates a dynamic threshold from the numerical values of the image obtained using the Intuitionistic fuzzy algorithm. By this means, the threshold value of each frame obtained from the camera was calculated on real time and implemented on the image timely. These algorithms were accelerated maximum 262 times using NVIDIA GTX 480 GPU supported display card.

  • Alam, I. J. (2013). Detecting Edge in an Image with the Help of Fuzzy Parameters. 11th International Conference on Frontiers of Information Technology, (pp. 19-24). Islamabad, Pakistan.Atanossov, K. (1986). Intuitionistic Fuzzy Sets. Fuzzy Sets and Systems, 20, 87-96.Bahri, H. S. (2017). Image feature extraction algorithm based on CUDA architecture: case study GFD and GCFD. IET Computers & Digital Techniques, 11(4), 125-132.Chaira, T. R. (2008). A new measure using intuitionistic fuzzy set theory and its application to edge detection. Applied Soft Computing, 8(2), 919–927.Chen, Z. X. (2010). A New High-Speed Foreign Fiber Detection System with Machine Vision. Mathematical Problems in Engineering, Article ID 398364, 15 pages.Fan, J. X. (1999). Distance measure and induced fuzzy entropy. Fuzzy Sets and Systems, 104, 305-314.Faujdar, N. G. (2017). A practical approach of GPU bubble sort with CUDA hardware. 7th International Conference on Cloud Computing (pp. 7-12). Noida: Data Science & Engineering.Gunes, M. B. (2016). Detecting Direction of Pepper Stem by Using CUDA-Based Accelerated Hybrid Intuitionistic Fuzzy Edge Detection and ANN. Journal of Sensors, 11 pages.Ji, R. L. (2010). Classification and Identification of Foreign Fibers in Cotton on the Basis of a Support Vector Machine. Mathematical and Computer Modelling, 51, 1433-1437.Kaushik, R. B. (2015). On Intuitionistic Fuzzy Divergence Measure with Application to Edge Detection. Procedia Computer Science, 70, 2-8.Liberman, M. A. (1998). Determining gravimetric bark content in cotton with machine vision. Textile Research Journal, 68(2), 94-104.Millman, M. P. (2001). Computer vision for textured yarn interlace (nip) measurements at high speeds. Mechatronics, 11(8), 1025-1038.NVIDIA, C. (2019). CUDA C Programming GUIDE. Retrieved from 9th Edition: https://docs.nvidia.com/cuda/cuda-c-programming-guide/Otsu, N. A. (1979). Threshold Selection Method from Gray-level Histograms. IEEE Transactions on Systems, Man and Cybernetic, 9(1), 62-66.Pal, N. R. (1992). Some Properties of the Exponential Entropy. Inform. Sci., 66, 119-137.Tastaswadi, P. V. (1999). Machine vision for automated visual inspection of cotton quality in textile industries using color isodiscrimination contour. Computer Industrial Engineering, 37(1-2), 347-350.Wang, X. Y. (2015). A fast image segmentation algorithm for detection of pseudo-foreign fibers in lint cotton. Comput. Electr. Eng., 46, 500-510.Xuecheng, L. (1992). Entropy, distance measure and similarity measure of fuzzy sets and their relations. Fuzzy Sets and Systems, 52, 305-318.Yang, W. Z. (2009). A new approach for image processing in foreign fiber detection. Computers and Electronics in Agriculture, 68(1), 68-77.Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8(3), 338–353.Zhang, H. L. (2014). Applications of computer vision techniques to cotton foreign matter inspection: A review. Computers and Electronics in Agriculture, 109, 59-70.Zhang, X. L. (2011). A fast Segmentation Method for High-Resulation Color Images of Foreign Fibers in Cotton. Computers and Electronics in Agriculture, 78, 71-79.
Primary Language en
Subjects Engineering, Electrical and Electronic
Journal Section Research Articles
Authors

Orcid: 0000-0002-4057-6069
Author: Eyüp Yalçın (Primary Author)
Institution: Kahramanmaras Sütcü Imam University
Country: Turkey


Orcid: 0000-0002-1552-3889
Author: Mahit GÜNEŞ
Institution: Kahramanmaras Sütcü Imam University
Country: Turkey


Supporting Institution Kahramanmaraş Sütçü İmam Üniversitesi
Project Number 2011/3-31YLS
Thanks This study was supported by the Scientific Research Project of Kahramanmaraş Sütçü Imam University with the code of 2011/3-31YLS
Dates

Application Date : July 30, 2019
Acceptance Date : November 4, 2019
Publication Date : November 29, 2019

Bibtex @research article { ksujes598920, journal = {Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi}, issn = {}, eissn = {1309-1751}, address = {}, publisher = {Kahramanmaras Sutcu Imam University}, year = {2019}, volume = {22}, pages = {95 - 108}, doi = {10.17780/ksujes.598920}, title = {GPU Accelerated Intuitionistic Fuzzy and Otsu Algorithms for Foreign Leaf Detection in Cotton}, key = {cite}, author = {Yalçın, Eyüp and GÜNEŞ, Mahit} }
APA Yalçın, E , GÜNEŞ, M . (2019). GPU Accelerated Intuitionistic Fuzzy and Otsu Algorithms for Foreign Leaf Detection in Cotton. Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi , 22 () , 95-108 . DOI: 10.17780/ksujes.598920
MLA Yalçın, E , GÜNEŞ, M . "GPU Accelerated Intuitionistic Fuzzy and Otsu Algorithms for Foreign Leaf Detection in Cotton". Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi 22 (2019 ): 95-108 <http://jes.ksu.edu.tr/en/issue/50210/598920>
Chicago Yalçın, E , GÜNEŞ, M . "GPU Accelerated Intuitionistic Fuzzy and Otsu Algorithms for Foreign Leaf Detection in Cotton". Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi 22 (2019 ): 95-108
RIS TY - JOUR T1 - GPU Accelerated Intuitionistic Fuzzy and Otsu Algorithms for Foreign Leaf Detection in Cotton AU - Eyüp Yalçın , Mahit GÜNEŞ Y1 - 2019 PY - 2019 N1 - doi: 10.17780/ksujes.598920 DO - 10.17780/ksujes.598920 T2 - Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi JF - Journal JO - JOR SP - 95 EP - 108 VL - 22 IS - SN - -1309-1751 M3 - doi: 10.17780/ksujes.598920 UR - https://doi.org/10.17780/ksujes.598920 Y2 - 2019 ER -
EndNote %0 Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi GPU Accelerated Intuitionistic Fuzzy and Otsu Algorithms for Foreign Leaf Detection in Cotton %A Eyüp Yalçın , Mahit GÜNEŞ %T GPU Accelerated Intuitionistic Fuzzy and Otsu Algorithms for Foreign Leaf Detection in Cotton %D 2019 %J Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi %P -1309-1751 %V 22 %N %R doi: 10.17780/ksujes.598920 %U 10.17780/ksujes.598920
ISNAD Yalçın, Eyüp , GÜNEŞ, Mahit . "GPU Accelerated Intuitionistic Fuzzy and Otsu Algorithms for Foreign Leaf Detection in Cotton". Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi 22 / (November 2019): 95-108 . https://doi.org/10.17780/ksujes.598920
AMA Yalçın E , GÜNEŞ M . GPU Accelerated Intuitionistic Fuzzy and Otsu Algorithms for Foreign Leaf Detection in Cotton. KSU J. Eng. Sci.. 2019; 22: 95-108.
Vancouver Yalçın E , GÜNEŞ M . GPU Accelerated Intuitionistic Fuzzy and Otsu Algorithms for Foreign Leaf Detection in Cotton. Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi. 2019; 22: 108-95.