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    •   BracU IR
    • School of Data and Sciences (SDS)
    • Department of Computer Science and Engineering (CSE)
    • Thesis & Report, BSc (Computer Science and Engineering)
    • View Item
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    2D Log gabor and SVD based parallel texture feature extraction usingNVIDIA GPU

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    12101092.pdf (2.919Mb)
    Date
    4/20/2016
    Publisher
    BRAC University
    Author
    Raja, Sharif Ahmmad
    Ratul, Aminur Rab
    Niloy, Sakib Anjum
    Metadata
    Show full item record
    URI
    http://hdl.handle.net/10361/5397
    Abstract
    Texture feature is one of the most popular technique in image segmentation, classification, retrieval and many others. Now a days, among other ways of texture feature extraction, Gabor filtering has been widely used. Here, we are presenting a well ordered two dimensional texture feature extraction method. First, we convert the image to gray level. Then a 2D Log Gabor filter with different frequencies decomposed with the SVD algorithm applies on each converted part of gray level image to extract appropriate distinctive texture information. To evaluate the performance of proposed model, we utilize singular values of SVD as a feature vector. For classifier, we use Naïve Bayes classifier for training and testing our experimental dataset. In our experimental set up we utilize an NVDIA GeForce GTX780 graphics card. Experimental result showed this parallel implementation of our model is56X faster than conventional CPU implementation.
    Keywords
    Computer science and engineering; CSE; NVIDIA GPU
     
    Description
    Cataloged from PDF version of thesis report.
     
    Includes bibliographical references (page 56-61).
     
    This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2016.
    Department
    Department of Computer Science and Engineering, BRAC University
    Collections
    • Thesis & Report, BSc (Computer Science and Engineering)

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