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IJSTR >> Volume 4 - Issue 2, February 2015 Edition

International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616

Image Reconstruction Using Pixel Wise Support Vector Machine (SVM) Classification.

[Full Text]



Mohammad Mahmudul Alam Mia, Rashedul Islam, Md. Ferdous Wahid, Shovasis Kumar Biswas



Index Terms: Neural networks, Classification, SVM, Kernel functions, Training set.



Abstract: Image reconstruction using support vector machine (SVM) has been one of the major parts of image processing. The exactness of a supervised image classification is a function of the training data used in its generation. In this paper, we studied support vector machine for classification aspects and reconstructed an image using support vector machine. Firstly, value of the random pixels is used as the SVM classifier. Then, the SVM classifier is trained by using those values of the random pixels. Finally, the image is reconstructed after cross-validation with the trained SVM classifier. Matlab result shows that training with support vector machine produce better results and great computational efficiency, with only a few minutes of runtime is necessary for training. Support vector machine have high classification accuracy and much faster convergence. Overall classification accuracy is 99.5%. From our experiment, It can be seen that classification accuracy mostly depends on the choice of the kernel function and best estimation of parameters for kernel is critical for a given image.



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