![]() ![]() ![]() To this end, in the present work, we have used Hausdorff and Fréchet distances to quantize the similarity among all possible word segments taking two at a time. However, no such work has been found which has considered inter-segment similarity that might carry some distinct information about different patterns (here, word segments). As observed in the literature related to handwritten word recognition, irrespective of the approaches, researchers generally extract various local features from hypothetically partitioned segments of a word image while dealing with the said problem. In this work, we have followed the holistic approach as it works well on limited and pre-defined lexicon as compared to the analytical approach. Two major approaches, namely holistic and analytical, are followed by the researchers while designing an HWR system. The reasons behind this are variations in intra-/interpersonal writing style, overlapping and/or touching characters in a word, degraded scanned document images, etc. The research community considers handwritten word recognition (HWR) as an open research problem to date. ![]()
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