A Novelty Approach on Tamil Spam Text Extraction by Using Texton Template Based Support Vector Machine and Lp Boosting Classifier
نویسندگان
چکیده
In this proposed method, the Tamil language texts are analyzed through the Morris-Pratt Algorithm as input image that filtered with Gabor filter for edge analysis. Then, it converted into unique strings from the text blocks. The text strings consist of text stroke to analyze the pattern. By using wavelet transform, the features of pattern are extracted and it undergoes for mapping with the texton patterns. It reduces the multiple dimensional signature patterns into reduced level. It then compared with the various image transformation methods such as DST (Discrete Shearlet Transform, DWT (Discrete Wavelet Transform and DCT (Discrete Cosine Transform that trained feature based on hybrid of SVM with Linear predictive boosting (LP boosting) algorithm. The effectiveness of the result is cross validated through confusion matrix and the result shows the proposed classifiers is more accurately predicts the tested Tamil text strings with reduced misclassification levels.
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