Performance Boost of Block Truncation Coding based Image Classification using Bit Plane Slicing | Zendy

H. B. Kekre | Zendy; Sudeep D. Thepade | Zendy; Rik Das | Zendy; Saurav Ghosh | Zendy

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Performance Boost of Block Truncation Coding based Image Classification using Bit Plane Slicing

Author(s) -

H. B. Kekre,

Sudeep D. Thepade,

Rik Das,

Saurav Ghosh

Publication year - 2012

Publication title -

international journal of computer applications

Language(s) - English

Resource type - Journals

ISSN - 0975-8887

DOI - 10.5120/7268-0447

Subject(s) - computer science , block truncation coding , slicing , coding (social sciences) , truncation (statistics) , block (permutation group theory) , bit plane , algorithm , artificial intelligence , image (mathematics) , arithmetic , computer graphics (images) , image compression , image processing , machine learning , statistics , mathematics , type (biology) , geometry , bit field , ecology , biology

Image classification demands major attention with increasing volume of available image data. The paper has shown performance boosting of image classification after associating Bit Plane Slicing with Block Truncation Coding (BTC) for feature extraction. Here more significant bit planes were considered for extraction of feature vectors. RGB color space was considered to carry out the experimentation. A database of 900 images was used for evaluation purpose. KeywordsPlane Slicing, BTC, CBIC, RGB

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