Classification and Recognition of Printed Hindi Characters Using Artificial Neural Networks

Indira, B.; M, Shalini; Murthy, M. V. Ramana; Shaik, Mahaboob Sharief

doi:10.5815/ijigsp.2012.06.03

Cited by 10 publications

(8 citation statements)

References 2 publications

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“…This approach needs to be applied carefully in order to avoid unexpected distortions or loss of data. In [2], a system for classification and recognition of printed Hindi vowels and consonants using artificial neural network is presented. The system consists of acquiring an image, step by step pre-processing, and then grouping of characters followed by recognition of characters.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Pattern recognition is a field concerned with machine recognition of meaningful irregularities in noisy and complex environment [2]. Pattern recognition aims to classify data (patterns) based on either prior knowledge or statistical information extracted from the patterns [5].Handwritten patterns recognition is of two types: online and offline as shown in Fig.…”

Section: Introductionmentioning

confidence: 99%

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Design of an Effective Preprocessing Approach for Offline Handwritten Images

Bhasin¹,

Goyal²,

Dutta³

2014

IJCA

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Handwritten pattern recognition involves conversion of scanned images of handwritten patterns into a computer processable form. To recognize handwritten patterns is an easy and trivial task for human beings, but for a machine it is a cumbersome and a difficult task due to high variations in the shape of characters and writing style. Although complicated to train, yet machines can be useful in providing solution to the recognition problem. They save time and money and eliminate the requirement of execution of repetitive tasks by humans. In order to have better recognition the image should be properly pre-processed. Pre-processing reduces and eliminates noise and irregularities. The present paper focuses on different approaches to pre-processing and an insight to general methodology for the recognition process. General TermsPattern Recognition

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Section: Literature Reviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Design of an Effective Preprocessing Approach for Offline Handwritten Images

Bhasin¹,

Goyal²,

Dutta³

2014

IJCA

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“…Many researchers applied a few methods for the recognition of characters like template matching, feature extraction, geometric approach, neural network, support vector machine, hidden Markov and Bayes net [26] [27].…”

Section: Literature Review On Lprmentioning

confidence: 99%

The Automatic License Plate Recognition (Alpr)

.¹

2013

IJRET

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All around the world the traffic police would stop drivers on the road to check if their road tax has been renewed. Unfortunately this sometimes causes delays for the people stopped and may even slow down the general traffic. Furthermore, for the police involved a big portion of their time is wasted just doing these checks. In this work we propose a new strategy for automating the monitoring of road-tax for drivers on the road and propose to notify the ones who need to renew their road tax by a formal e-mail message.The idea is to combine the license plate detection and recognition process with the driver's information stored in a database and an e-mail sending function. The first task is the acquisition of frontal images for approaching cars. Then the application will estimate the rotation angle on each frame and make it horizontal by reverse transforming it. Subsequently, the position of the license plate in the frame will be detected and it will be segmented out. Once the plate region is cropped out the next step will be to segment out the individual alpha numeric characters. This task is achieved by looking at a vertical projection profile. Later the characters are traced to obtain their associated stroke based (8-connectivity) chain codes. Finally features are extracted from characters and chain codes and character recognition is carried out based on the collected features.Our hybrid license plate detection and recognition system was tested using 150 test images. With two-letter and three-digit notation of North Cyprus license plates this would mean around 750 characters. Simulation results have showed that our iv proposed system was 93.33% successful in detecting and segmenting out the license plates. For detected plates the character segmentation accuracy was 100% and the recognition accuracy was 96.42%. Finally our ALPR system was found 92.85% successful in recognizing vehicle license plates. Note that only the cases where all characters were correctly detected have been considered as correctly recognized plate.After obtaining the plate number a database is searched to locate the owner of the vehicle. The name obtained will then be used to check the road tax statue of the driver and if necessary an automatic e-mail message will be sent out using the e-mail

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“…Challenges in handwritten signatures recognition lie in the variation and distortion of handwritten signatures, since different people may use different style of handwriting and direction to draw the same shape of any character (Hindi Characters: [2,11,9]), English Characters: [6,7,14]). …”

Section: Introductionmentioning

confidence: 99%

Offline Handwriting Recognition Using Feedforward Neural Network

Rosalina¹,

Wahyu²

2017

IJITCS

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Abstract-Many business especially Banks"s services are expanding to include services directed not only to corporate customers but also to individual customer. Furthermore, by the increment of those services, many individual applications to be processed also increases as well. Facing an immense moment, in which requiring more improvements in how it should manage or maintain its applications, some systems or procedures must be improved to match currently increasing customers" applications. Prior to the improvements, many application forms are filled, input to machine and even to be processed and approved manually. Until recently, application fulfillment processes consists of manual information filling by applicants in an application request paper and later to be re-input by electronic data processing staff which is actually redundant. Aware of such situation, this paper proposes and idea to reduce input processes in an integrated business system by utilizing character recognition system.

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Classification and Recognition of Printed Hindi Characters Using Artificial Neural Networks

Cited by 10 publications

References 2 publications

Design of an Effective Preprocessing Approach for Offline Handwritten Images

Design of an Effective Preprocessing Approach for Offline Handwritten Images

The Automatic License Plate Recognition (Alpr)

Offline Handwriting Recognition Using Feedforward Neural Network

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