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Home / programming language / Online Matlab Projects / Object recognition using rotation invariant local binary pattern of significant bit planes
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Object recognition using rotation invariant local binary pattern of significant bit planes

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SKU: PROJ7490 Categories: 2017 Projects, Final Year Projects, Digital Image Processing Projects, programming language, Online Matlab Projects Tags: Android Project, Asp.Net Project, C# Project, Computer Engineering Final Year Projects, Computer Science Final Year Projects, Electronics Projects Engineering Students Final Year, Engineering Student Project Ideas, Final Semester Projects, Final Year Project Center, Final Year Projects, ieee ECE Projects, ieee EEE Projects, ieee Final Year Projects, IEEE Projects, ieee Projects Networking, Image Processing Projects, J2EE Project, Java Project, Java Project Code, Matlab Project, PHP Project, Students Projects
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Object recognition using rotation invariant local binary pattern of significant bit planes

Abstract— The binary feature descriptors such as binary robust independent elementary features (BRIEF), oriented rotated binary robust independent elementary features (ORB), and fast retina keypoint (FREAK) usually perform binarisation on the intensity comparisons, thus they lo se some useful information. In this study, the authors propose an effective binary image descriptor which is called significant bit-planes-based local binary pattern for visual recognition. First, the authors divide an image into several sub regions according to the intensity orders to incorporate the spatial information . Then the authors extract the higher bit planes for all the sub regions and sort the adjacent neighbour bits based on the corresponding intensity orders, which make the descriptor invariant to rotation. In order to further improve the discriminative ability , the authors sample the multi-scale neighbours and average the adjacent pixels and extract the feature descriptor from the higher bit planes. Since the authors directly perform operation on the significant bit planes without quantisation, the authors decrease the information loss to some extent. < final year projects >

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