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Artificial Neural Network (ANN) s has widely been used for recognition ofoptically scanned character, which partially emulates human thinking in thedomain of the Artificial Intelligence. But prior to recognition, it isnecessary to segment the character from the text to sentences, words etc.Segmentation of words into individual letters has been one of the majorproblems in handwriting recognition. Despite several successful works all overthe work, development of such tools in specific languages is still an ongoingprocess especially in the Indian context. This work explores the application ofANN as an aid to segmentation of handwritten characters in Assamese- animportant language in the North Eastern part of India. The work explores theperformance difference obtained in applying an ANN-based dynamic segmentationalgorithm compared to projection- based static segmentation. The algorithminvolves, first training of an ANN with individual handwritten charactersrecorded from different individuals. Handwritten sentences are separated outfrom text using a static segmentation method. From the segmented line,individual characters are separated out by first over segmenting the entireline. Each of the segments thus obtained, next, is fed to the trained ANN. Thepoint of segmentation at which the ANN recognizes a segment or a combination ofseveral segments to be similar to a handwritten character, a segmentationboundary for the character is assumed to exist and segmentation performed. Thesegmented character is next compared to the best available match and thesegmentation boundary confirmed.

ANN-based Innovative Segmentation Method for Handwritten text in Assamese