Design of Novel Feature Vector for Recognition of Online Handwritten Bangla Basic Characters

摘要

In the present work, a new feature vector has been designed towards recognition of handwritten online Bangla basic characters. At first, Center of Gravity (CG) of a particular character sample is determined. After that a circle enclosing the character sample is drawn whose radius is estimated as the distance of farthest data pixel from that CG. From this circular region, a 136-element feature vector is generated considering both the global as well as local information of the character sample. The feature set has been tested with several well-known classifiers on 10,000 isolated Bangla basic characters. Finally, Support Vector Machine (SVM) has produced 98.26 % recognition accuracy.