Offline Handwritten Devanagari Word Recognition: A Holistic Approach Based on Directional Chain Code Feature and HMM

Shaw, Bikash; Parui, Susanta Kumar; Shridhar, M.

doi:10.1109/icit.2008.33

Cited by 46 publications

(13 citation statements)

References 9 publications

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“…Bikash Shaw et al presented an offline handwritten Devnagari word recognition: a segmentation based approach for recognition handwritten Devnagari words. Stroke based features are used as feature vectors and hidden Markov model is used for recognition [21]. J. Pradeep,presented a handwritten character recognition system using multilayer Feed forward neural network.…”

Section: Review Of Feature Extraction Methodsmentioning

confidence: 99%

A Novel Approach Towards Online Devnagari Handwritten Word Recognition Based on Robust Feature Extraction Method and FFNN Classifier.

Ansari¹,

Bhavani²,

Sutar³

2017

IJAR

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Section: Review Of Feature Extraction Methodsmentioning

confidence: 99%

A Novel Approach Towards Online Devnagari Handwritten Word Recognition Based on Robust Feature Extraction Method and FFNN Classifier.

Ansari¹,

Bhavani²,

Sutar³

2017

IJAR

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“…A continuous density HMM is also proposed by Shaw et al [20] to recognize a handwritten word images. The states of the HMM are not determined a priori, but are determined automatically based on a database of handwritten word images.…”

Section: Post-processingmentioning

confidence: 99%

A Review on Offline Handwritten Recognition of Devnagari Script

Patwardhan¹,

Deshmukh²

2015

IJCA

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“…For each block, L2 norm is calculated. Therefore, each block from the original image can be represented by a feature vector of (5 orientation × 3 scales) [14]. …”

Section: Fig4 Log Gabor Filter Images Of Charactermentioning

confidence: 99%

Exploration of Improved Methodology for Character Image Recognition of Two Popular Indian Scripts using Gabor Feature with Hidden Markov Model

Saxena¹,

Dhaka²

2015

IJCA

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Handwritten character recognition plays an important role in the modern world. It can solve more complex problems and make the human's job easier. The present work portrays a novel approach in recognizing handwritten cursive character using Hidden Markov Model (HMM) . The method exploits the HMM formalism to capture the dynamics of input patterns, by applying a Gabor filter to a character image, observation feature vector is obtained, and used to form feature vectors for recognition. The HMM model is proposed to recognize a character image. All the experiments are conducted by using the Matlab tool kit.

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Offline Handwritten Devanagari Word Recognition: A Holistic Approach Based on Directional Chain Code Feature and HMM

Cited by 46 publications

References 9 publications

A Novel Approach Towards Online Devnagari Handwritten Word Recognition Based on Robust Feature Extraction Method and FFNN Classifier.

A Novel Approach Towards Online Devnagari Handwritten Word Recognition Based on Robust Feature Extraction Method and FFNN Classifier.

A Review on Offline Handwritten Recognition of Devnagari Script

Exploration of Improved Methodology for Character Image Recognition of Two Popular Indian Scripts using Gabor Feature with Hidden Markov Model

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