Comparative Analysis Of Dimension Reduction Technique In CBMR Systems
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Abstract
Content Based Multimedia Retrieval is the upcoming area used to obtain descriptive features resulting in the form of huge feature count and processing overhead. The different dimension reduction methods are used to reduce the feature count and descriptive feature overhead, PCA Principle component Analysis, LDA Linear Discriminate Analysis, MLK Multi linear kernel Modeling are used were the histogram transformation features are used to eliminate the low significance features. The paper discusses about the comparison of the three dimension reduction technique, The benchmark data set is used for experimental result and to achieve the performance and accuracy they are taken for an analysis and compared among the three methods.
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