Offline handwritten Arabic cursive text recognition using Hidden Markov Models and re-ranking

Offline Handwritten Arabic Cursive Text Recognition using 1 Hidden Markov Models and Re - ranking 2 3 4

Offline Handwritten Arabic Cursive Text Recognition using 12 Hidden Markov Models and Re - ranking 13

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A multi-stream hmm approach to offline handwritten arabic word recognition

In This paper we presented new approach for cursive Arabic text recognition system. The objective is to propose methodology analytical offline recognition of handwritten Arabic for rapid implementation. The first part in the writing recognition system is the preprocessing phase is the preprocessing phase to prepare the data was introduces and extracts a set of simple statistical features by two...

Off-line Arabic Handwritten Recognition Using a Novel Hybrid HMM-DNN Model

In order to facilitate the entry of data into the computer and its digitalization, automatic recognition of printed texts and manuscripts is one of the considerable aid to many applications. Research on automatic document recognition started decades ago with the recognition of isolated digits and letters, and today, due to advancements in machine learning methods, efforts are being made to iden...

Recognising handwritten Arabic manuscripts using a single hidden Markov model

This paper presents a new method on off-line recognition of handwritten Arabic script. The method does not require segmentation into characters, and is applied to cursive Arabic script, where ligatures, overlaps and style variation pose challenges to the recognition system. The method trains a single hidden Markov model (HMM) with the structural features extracted from the manuscript words. The...