A holistic word recognition technique for handwritten Bangla words

Holistic word recognition is the current trend for handwritten word recognition. The holistic paradigm in handwritten word recognition considers a word as a single, indivisible entity and attempts to recognise words from their overall shape unlike recognising the individual characters comprising the word. In the present work, concentric rectangles and convex hull-based features are designed in order to classify word images belonging to different classes. For the evaluation of the current technique, 2,754 handwritten Bangla word samples are collected from different sources. A neural network-based classifier is chosen on the basis of the performances of different classifiers and some statistical tests. The recognition performance of the technique is evaluated using a three-fold cross-validation method. From the experimental results, it is observed that the proposed technique correctly recognises 84.74% word images in best case.