Handwritten Bangla Word Recognition Using HOG Descriptor
Showmik Bhowmik, Md. Galib Roushan, Ram Sarkar, Mita Nasipuri, Sanjib Polley, Samir Malakar · 2014
The holistic approaches for handwritten word recognition treat the words as single, indivisible entity and attempt to recognize words from their overall shape. In the present work, a novel technique to recognize handwritten Bangla word is proposed. Histograms of Oriented Gradients (HOG) are used as the feature set to represent each word sample at the feature space and a neural network based classifier is applied to classify the word images. On the basis of the HOG feature set, the performance achieved by the technique on a small dataset is quite satisfactory.