Object Recognition using Discriminative Robust Local Binary Pattern
نویسندگان
چکیده
Local Binary Pattern is the most popular texture classification feature. It also shows excellent face detection performance. It is robust to the illumination and contrast variations as it considers the signs of the pixel differences. A Histogramming Local Binary Pattern code makes the descriptor resistant to translations within the Histogramming neighborhood. The two sets of novel edge-texture features are been proposed in this paper that are Discriminative Robust Local Binary Pattern (DRLBP) and Discriminative Robust Ternary Pattern (DRLTP). DRLBP helps to resolves the problem of Robust Local Binary Pattern in which the Local Binary Pattern codes and their complements which are in the same block area been mapped to the same code. Further, the proposed features also tend retain contrast information that is necessary for proper representation of the object contours.
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