Off-line Handwritten Character Recognition using Hidden Markov Model

被引：0

作者：

Gayathri, P. ^{[1
]}

Ayyappan, Sonal ^{[1
]}

机构：

[1] SCMS Sch Engn & Technol, Dept Comp Sci & Engn, Ernakulam, Kerala, India

来源：

2014 INTERNATIONAL CONFERENCE ON ADVANCES IN COMPUTING, COMMUNICATIONS AND INFORMATICS (ICACCI) | 2014年

关键词：

Handwritten character recognition; Hidden Markov Model; Optical Character Recognition; Binarization; Normalization; Pre-processing; Feature Extraction;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

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.

引用

页码：518 / 523

页数：6

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