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Support Vector Machine, Projection Histogram for Math Expression   Pallavi Baviskar

Support Vector Machine, Projection Histogram for Math Expression

92 страниц. 2013 год.
LAP Lambert Academic Publishing
This book provides information about mathematical expression recognition with one of the best technique for recognition and classification. Mathematical symbols and operators are represented in same way in different languages, which is useful to most of the researchers who work on character recognition in various languages. Projection histogram is used for extracting features from each sample. Using horizontal and vertical projection minimum ten features are extracted.Recognition of handwritten mathematical symbols and expression is difficult task due to different way of writing styles so support vector machine can beneficial classifier. most of researchers have been use this feature extraction technique and classifier. Using this method 98.40% recognition rate is achieved.
 
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