Offline cursive script recognition current advan

Authors: Amjad Rehman Tanzila Saba

Publish Date: 2011/05/10

Volume: 37, Issue: 4, Pages: 261-288

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Abstract

This paper presents detailed review in the field of offline cursive script recognition Various methods are analyzed that have been proposed to realize the core of script recognition in a word recognition system These methods are discussed in view of the two most important properties of such systems size and nature of the lexicon involved and whether or not a segmentation stage is present Script recognition techniques are classified into three categories firstly segmentationfree methods or holistic approaches that compare a sequence of observations derived from whole word image with similar references of words in the small lexicon Secondly segmentationbased methods that look for the best match between consecutive sequences of primitive segments and letters of a possible word similar to humanlike reading technique in which secure features found all over the word are used to bootstrap a few candidates for a final evaluation phase thirdly hybrid approaches Additionally different feature extraction techniques are elaborated in conjunction with the classification process In this scenario implications of single and multiple classifiers are also observed Finally remaining problems are highlighted along with possible suggestion and strategies to solve them

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