Segmentation of Words From Unconstrained Multilingual Hand written Documents

In this work an efficient technique for segmenting the words from multilingual unconstrained handwritten documents is proposed. In the proposed model, morphological operations and connected component analysis are used for word identification. Based on identification bounding box for every word is drawn and then words are segmented. The proposed algorithm also works on documents with any orientation. We conducted experimentation on 500 unconstrained multilingual handwritten documents. The result shows that the performance of the proposed algorithm is good.