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Automated text analysis and mining tools designed to identify the main topics of texts, chat room discussions, and web postings are an increasingly active research area due to the rapid explosion of Web information. This paper applies the nonlinear kernel-based Feature Vector Selection (FVS) approach followed by a Linear Discriminant Analysis (LDA) step to categorize unstructured text documents. Results...
In real imaging system, the observed image is usually corrupted by blurring, spatial degradations. The classical recognition methods in degraded image analysis are to obtain blur invariants based on geometric moments or complex moments. In this paper, we introduce blur invariants based on Zernike moments which are orthogonal over a unit circle. Both the expression of Zernike moments of blurred image...
Road and traffic sign recognition has been of great interest for many years. This paper presents an approach to recognize Swedish road and traffic signs by using support vector machines. We focus on recognizing seven categories of traffic sign shapes and five categories of speed limit signs. Two kinds of features, binary image and Zernike moments, are used for representing the data to the SVM for...
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