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dc.contributor.advisorUddin, Jia
dc.contributor.authorRaja, Sharif Ahmmad
dc.contributor.authorRatul, Aminur Rab
dc.contributor.authorNiloy, Sakib Anjum
dc.date.accessioned2016-05-26T12:21:36Z
dc.date.available2016-05-26T12:21:36Z
dc.date.copyright2016
dc.date.issued4/20/2016
dc.identifier.otherID 12101092
dc.identifier.otherID 12101116
dc.identifier.otherID 12101085
dc.identifier.urihttp://hdl.handle.net/10361/5397
dc.descriptionCataloged from PDF version of thesis report.
dc.descriptionIncludes bibliographical references (page 56-61).
dc.descriptionThis thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2016.en_US
dc.description.abstractTexture 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.en_US
dc.description.statementofresponsibilitySharif Ahmmad Raja
dc.description.statementofresponsibilityAminur Rab Ratul
dc.description.statementofresponsibilitySakib Anjum Niloy
dc.format.extent31 pages
dc.language.isoenen_US
dc.publisherBRAC Universityen_US
dc.rightsBRAC University thesis are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission.
dc.subjectComputer science and engineeringen_US
dc.subjectCSEen_US
dc.subjectNVIDIA GPUen_US
dc.title2D Log gabor and SVD based parallel texture feature extraction usingNVIDIA GPUen_US
dc.typeThesisen_US
dc.contributor.departmentDepartment of Computer Science and Engineering, BRAC University
dc.description.degreeB. Computer Science and Engineering


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