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An Efficient VLSI Design for Extracting Local Binary Pattern
Abstract— The nonspecific nature of the signs and symptoms of Acute Myelogenous leukaemia typically results in wrong designation. Diagnostic confusion is additionally display because of imitation of comparable signs by alternative disorders. Careful microscopic examination of stained blood smear or bone marrow aspirate is that the solely thanks to effective designation of leukaemia. Now a days, a statistic approach to texture analysis has been developed, during which the distributions of straightforward texture measures supported native ternary patterns (LTP) are used for texture details. This paper shows that a selected set of patterns encoded in LTP forms together with wavelets transform primarily based frequency domain parameters extraction is an economical and sturdy texture description which may bring higher classification rates compared with the prevailing ways.
Index Terms -- Acute myelogenous leukemia (AML), classification, color conversion, feature extraction, segmentation
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International Journal for Trends in Technology & Engineering © 2015 IJTET JOURNAL