Shape Feature and Fuzzy Logic Based Offline Devnagari Handwritten Optical Character Recognition

Mukherji, Prachi; Rege, Priti P.

doi:10.13176/11.48

Cited by 25 publications

(17 citation statements)

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“…The segments of characters are coded using Average Compressed Direction Code algorithm. With top modifier 71.68 % and without top modifier 88.33% accuracy is achieved [5]. Sandhya Arora et.al presented a scheme for online Handwritten Devnagari Character Recognition, which uses different feature extraction and recognition algorithms.…”

Section: Review Of Devnagari Character Recognition 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 Devnagari Character Recognition 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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“…Feature sets used in the classifiers calculated the curvature and gradient information acquired from binary as well as gray-scale images. Mukherji and Rege [11] proposed a shape based technique for recognition of isolated handwritten Devanagari characters. The position in the image frame was based on fuzzy classification.…”

Section: A Survey On Offline Handwritten Hindi Character Recognitionmentioning

confidence: 99%

Offline Handwritten Hindi 'SWARs' Recognition Using A Novel Wave Based Feature Extraction Method

2017

IJCSI

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Offline handwritten character recognition is a very challenging area of research as handwriting of two persons may bear resemblance whereas handwriting of an individual may vary at different times. The character recognition accuracy depends on the ways the features are extracted from the samples and utilized to formulate the feature vector. In this paper, a novel technique 'TARANG' for feature extraction is proposed to recognize offline handwritten Hindi 'SWARs' (vowels). This technique for extracting features from an image is inspired by the natural movement of wave in a medium. A feature vector obtained by using proposed technique is used for the training of Backpropagation Neural Network and recognition rate as high as 96.2% is achieved.

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“…Image is represented either by graphs coordinates of the character shape or by an abstract representation with nodes corresponding to the strokes and edges corresponding to the relationships between the strokes. Trees can also be used to represent the words or characters with a set of features, which has a hierarchical relation [49][50][51].…”

Section:  Measuring and Approximating The Geometrical Propertiesmentioning

confidence: 99%

A Review on Feature Extraction and Feature Selection for Handwritten Character Recognition

Mohamad¹,

Hassan²,

Nasien³

et al. 2015

ijacsa

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Abstract-The development of handwriting character recognition (HCR) is an interesting area in pattern recognition.HCR system consists of a number of stages which are preprocessing, feature extraction, classification and followed by the actual recognition. It is generally agreed that one of the main factors influencing performance in HCR is the selection of an appropriate set of features for representing input samples. This paper provides a review of these advances. In a HCR, the set of features plays as main issues, as procedure in choosing the relevant feature that yields minimum classification error. To overcome these issues and maximize classification performance, many techniques have been proposed for reducing the dimensionality of the feature space in which data have to be processed. These techniques, generally denoted as feature reduction, may be divided in two main categories, called feature extraction and feature selection. A large number of research papers and reports have already been published on this topic. In this paper we provide an overview of some of the methods and approach of feature extraction and selection. Throughout this paper, we apply the investigation and analyzation of feature extraction and selection approaches in order to obtain the current trend. Throughout this paper also, the review of metaheuristic harmony search algorithm (HSA) has provide.

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Shape Feature and Fuzzy Logic Based Offline Devnagari Handwritten Optical Character Recognition

Cited by 25 publications

References 0 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.

Offline Handwritten Hindi 'SWARs' Recognition Using A Novel Wave Based Feature Extraction Method

A Review on Feature Extraction and Feature Selection for Handwritten Character Recognition

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