Publication | Closed Access
Off-line handwritten character recognition using Hidden Markov Model
13
Citations
6
References
2014
Year
Unknown Venue
Machine VisionImage AnalysisMachine LearningMalayalam Handwritten VowelsPattern RecognitionEngineeringBiometricsHidden Markov ModelText RecognitionFeature ExtractionPattern Recognition ApplicationArabic OrthographyComputer ScienceStatistical Pattern RecognitionCharacter RecognitionOptical Character RecognitionSpeech Recognition
In this paper, we are presenting a method for the recognition of Malayalam handwritten vowels using Hidden Markov Model (HMM). OCR is a method to detect characters in different sources. The goal of OCR is to classify optical patterns in an image to the corresponding characters. Recognition of handwritten Malayalam vowels is proposed in this paper. Images of the characters written by eighteen subjects are used for this experiment. Training and recognition are performed using Hidden Markov Model Toolkit. Recognition process involves several steps including image acquisition, dataset preparation, pre-processing, feature extraction, training and recognition. An average accuracy of about 81.38% has been obtained.
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