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Fisher discrimination dictionary sparse learning (FDDL) has led to interesting image recognition results where the Fisher discrimination criterion is subject to the coding coefficients. But Fisher discrimination criterion has the limitations of data distribution assumptions and does not consider the local manifold structure of the coding coefficients. In this paper, we will introduce a novel Fisher...
This paper introduces a multi-class classification algorithm based on sparse representation which considers on rejection option to minimize risks caused by outliers. Here the outliers include signals that do not belong to any classes learned in a training step. To successfully reject the outliers, new rejection measure and corresponding dictionary learning algorithm are presented. Experimental results...
Text detection in images is important for the retrieval of text information from digital graph, video databases and web sites. In this paper, a text detection method based on sparse representation classification with discrimination dictionaries is presented, which can detect text with different sizes, fonts and colors. The propose method detects edge information using Sobel operator and a sliding...
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