Editor/Reviewer loginFrequency : 12 issues per year
Subject : Computer Applications and Technology
ISSN : 2319–8656 (Online)
IJCATR Volume 5 Issue 3
Holistic Approach for Arabic Word Recognition
Talaat M. Wahbi Mohamed E. M. Musa
10.7753/IJCATR0503.1005
keywords : pattern recognition; HMM; Holistic approach; offline recognition: Arabic word recognition
Optical Character Recognition (OCR) is one of the important branches. One segmenting words into character is one of the most challenging steps on OCR. As the results of advances in machine speeds and memory sizes as well as the availability of large training dataset, researchers currently study Holistic Approach “recognition of a word without segmentation”. This paper describes a method to recognize off-line handwritten Arabic names. The classification approach is based on Hidden Markov models.. For each Arabic word many HMM models with different number of states have been trained. The experiments result are encouraging, it also show that best number of state for each word need careful selection and considerations.
@artical{t532016ijcatr05031005,
Title = "Holistic Approach for Arabic Word Recognition",
Journal ="International Journal of Computer Applications Technology and Research(IJCATR)",
Volume = "5",
Issue ="3",
Pages ="141 - 146",
Year = "2016",
Authors ="Talaat M. Wahbi
Mohamed E. M. Musa"}
Arabic handwriting recognition is far behind other similar languages, more research is needed.
Evaluation of skipping segmentations and recognizing a whole word.
Using and Presenting a new promising Arabic word dataset .
Searching for the best Hidden Markov number of states for specific application.