Cuda Based Fuzzy C-Means Acceleration for the Segmentation of Images with Fungus Grown in Foam Matrices

• Autorzy: Rowińska, Z. , Gocławski, J.
• Języki publikacji: EN

Abstrakty

EN

In the paper authors verify the advantages of GPU computing applied to fuzzy c-means segmentation. Three different algorithms implementing FCM method have been compared by their execution times. All tests refer to the images of polyurethane foam matrices filled with fungus (mould). They are aimed at separating mould regions from the matrix base. The authors proposed a method using CUDA programming tools, which significantly speedsup FCM computations with multiple cores built in a graphic card.

Słowa kluczowe

EN

GPU computing; fuzzy c-means algorithm; FCM

• Czasopismo: Image Processing & Communications
• Rocznik: 2012
• Tom: Vol. 17, no. 4
• Strony: 191--200
• Opis fizyczny: Bibliogr. 11 poz., rys., tab.

Twórcy

autor

Rowińska, Z.

• Institute of Applied Computer Science Lodz University of Technology,

autor

Gocławski, J.

• Institute of Applied Computer Science Lodz University of Technology

Bibliografia

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• [4] E.R. Gonzalez, R E. Woods, S.L. Eddins, Digital Image Processing Using MATLAB, Prentice Hall, Upper Saddle River, NJ, 2004
• [5] D. Graves, W. Pedrycz, Fuzzy C-Means, Gustafson- Kessel FCM, and Kernel-Based FCM: A Comparative Study, Analysis and Design of Intelligent Systems using Soft Computing Techniques, Vol. 41, pp. 140- 149, 2007
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• [7] J. Sanders, T. Kandrot, CUDA by Example: An Introduction to General-Purpose GPU Programming, NVIDIA Corporation, 2011
• [8] The Mathworks Inc., Fuzzy logic toolbox, http://www.mathworks.com/help/toolbox/fuzzy/fp310.html
• [9] The Mathworks Inc., MEX-files Guide, http://www.mathworks.com/support/technotes/1600/1605.html
• [10] The Mathworks Inc., Documentation Center, Parallel Computing Toolbox, http://www.mathworks.com/help/distcomp/index.html
• [11] NVIDIA: GPU Acceleration on MATLAB with Jacket, http://www.nvidia.com/object/teslajacket-gpu-acceleration.html