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Handwritten Digit Recognition using Image Processing

Team membersAnita Maharjan(102/067/BEX)Chetana Moktan(108/067/BEX)

(A presentation of a case study on title)

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Overview

• Introduction• Objective• Implementation• System Overview• Neural Network• Conclusion

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Introduction

• This working prototype system can detect handwritten digits from a scanned image of an input form by using Neural network technique.

• very fast and effective as compared to old fashioned image pixel comparison methodology.

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Objective

• To recognize handwritten digits in real works for autonomous machine processing.

• To be familiar to Neural Networks

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Application

Signature Recognition Currency Recognition

Number Plate Recognition House no. Recognition

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System Overview

Handwritten digit image collection

Image cut and store

Image Slice

Convert to standard size

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Calculate HH,VH,LDH,RDH

Calculate GH=HH+VH+LDH+RDH

Maintain Database

Training Neural Network

Digit Recognition

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Neural Network

• Back Propagation Method• Hidden layer• Sigmoid activation function,

O(i)=1/(1+e^(input))

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Neural Network(Continue)

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Conclusion

• Thus, understanding of neural networks• we have more control over its applications • now easy to implement such intelligence to

identify objects into machines and computers • In order to cater our needs in the industrial

applications

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Reference

• Faisal Tehseen Shah, Kamran Yousaf*, “Handwritten Digit Recognition Using Image Processing and Neural Networks”

• Youssef Es Saady, Ali Rachidi, Mostafa El Yassa, Driss Mammass , “Amazigh Handwritten Character Recognition based on Horizontal and Vertical Centerline of Character” , International Journal of Advanced Science and Technology, Vol. 33

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Thank You!!