On-line Handwritten character Recognition using Kohonen networks

Sreeraj, M; Idicula, Sumam Mary

doi:10.1109/nabic.2009.5393707

Cited by 8 publications

(5 citation statements)

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“…Tablet is a powerful tool as the input of handwriting because tablet can receive both text and graphics. There are many electronic devices that can be used as a tool in Handwriting recognition such as a mobile device/smartphone [11,12,13]. Research on the utilization of input devices such as electronic pen was also conducted by Sreeraj [14].…”

Section: B Handwriting Recognitionmentioning

confidence: 99%

Handwritten Pattern Recognition Using Kohonen Neural Network Based on Pixel Character

Munggaran¹,

Widodo²,

A.M³

et al. 2014

ijacsa

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Abstract-Handwriting is the human way in communicating each other using written media. By the advancement in technology and development of science, there are a lot of changes of technology in terms of communication with computer through handwriting. Therefore, it is needed computer able to receive input in the form of handwriting data and able to recognize the handwriting input. Therefore, this research focuses on handwritten character recognition using Kohonen neural network. The purpose of this research is to find handwriting recognition algorithm which can receive handwriting input and recognize handwritten character directly inputted in computer using Kohonen neural network. This method studies the distribution of a set of patterns without any class information. The basic idea of this technique is understood from how human brain stores images/patterns that have been recognized through eyes, and then able to reveal the images/patterns back. This research has been successful in developing an application to recognize handwritten characters using Kohonen neural network method, and it has been tested. The application is personal computer based and using a canvas as input media. The recognition process consist of 3 stages layer: Input layer, Training Layer and Hidden Layer. The Kohonen neural network method on handwritten character recognition application has good similarity level of character patterns in character mapping process.

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Section: B Handwriting Recognitionmentioning

confidence: 99%

Handwritten Pattern Recognition Using Kohonen Neural Network Based on Pixel Character

Munggaran¹,

Widodo²,

A.M³

et al. 2014

ijacsa

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“…Centroid of the image is also taken to improve the result. Online system which uses a combination of context bitmap and normalised (x,y) co-ordinates has also been developed [3]. It uses Kohonen network for recognition.…”

Section: Related Workmentioning

confidence: 99%

Freeman Code Based Online Handwritten Character Recognition for Malayalam using Backpropagation Neural Networks

Sampath¹

2012

ACIJ

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Handwritten character recognition is conversion of handwritten text to machine readable and editable form. Online character recognition deals with live conversion of characters. Malayalam is a language spoken by millions of people in the state of Kerala and the union territories of Lakshadweep and Pondicherry in India. It is written mostly in clockwise direction and consists of loops and curves. The method aims at training a simple neural network with three layers using backpropagation algorithm.Freeman codes are used to represent each character as feature vector. These feature vectors act as inputs to the network during the training and testing phases of the neural network. The output is the character expressed in the Unicode format.

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“…(i) Characters can be viewed as composition of strokes. [2], [3], [4], [5], [6] (ii) Characters may be viewed as compositions of C, C', V and M graphemes [7] (iii) character can be viewed as indivisible units. [8].…”

Section: Related Workmentioning

confidence: 99%