Offline Tamil Handwritten Character Recognition Using Sub Line Direction and Bounding Box Techniques

Character recognition plays an important role in the field of pattern recognition. Offline character recognition methodology mainly focuses on recognizing the characters irrespective of the difficulties that may arise due to the variations in writing style. This writing style becomes more complex when the characters are in curvy structure. The proposed recognition methodology was applied on one of the complex structures of south Indian language 'Tamil'. The novelty behind this process lies on the selection and extraction of the feature sets. Zoning and Chain Code procedures are employed here to select the features and Sub Line Direction and Bounding box algorithms are used for extracting the features. In order to achieve a better recognition rate, a learning algorithm, Support Vector Machine (SVM) has been implemented. These concepts are experimented on 30 Tamil character sets (Vowels and Consonants) and achieved an accuracy rate of 88%.