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In image based feature descriptor design, local information from imagepatches are extracted using iterative scanning operations which cause highcomputational costs. In order to avoid such scanning operations, we presentmatrix multiplication based local feature descriptors, namely a Matrixprojection based Local Binary Pattern (M-LBP) descriptor and a Matrixprojection based Histogram of Oriented Gradients (M-HOG) descriptor.Additionally, an integrated formulation of M-LBP and M-HOG (M-LBP-HOG) is alsoproposed to perform the two descriptors together in a single step. The proposeddescriptors are evaluated using a publicly available mammogram database. Theresults show promising performances in terms of classification accuracy andcomputational efficiency.

An LBP-HOG Descriptor Based on Matrix Projection For Mammogram Classification