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OPTICAL CHARACTER

RECOGNISITION USING MACHINE

LEARNING

PRESENTATION

ON

PRESENTED BY

PRANAV KUMAR PANDEY

2014JID2860

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OBJECTIVES OF PROJECT

Implementing a algorithm for recognizing the characters or

test in a given image or recognizing the test capture from

the mobile camera

2

Difficulties in Character Recognition with varying

background, lighting condition, text orientation and

font.

Computational power of mobile platform

COMPLEXITIES INVOLVED

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PLAN OF PROJECT

Literature SurveyComparison of various machine learning algorithms

Supervised Learning : Multilayer ANN

Unsupervised Learning

Deep Learning

Implementation of algorithm using Matlab

Implementing algorithm on mobile platform

3

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REFERENCES

Coates, Adam, Blake Carpenter, Carl Case, Sanjeev

Satheesh, Bipin Suresh, Tao Wang, David J. Wu, and

Andrew Y. Ng. "Text detection and character recognition in

scene images with unsupervised feature learning."

InDocument Analysis and Recognition (ICDAR), 2011

International Conference on, pp. 440-445. IEEE, 2011.

H. Lee, R. Grosse, R. Ranganath, and A. Y. Ng,

Convolutional deep belief networks for scalable

unsupervised learning of hierarchical representations, in

International Conference on Machine Learning, 2009.

T. E. de Campos, B. R. Babu, and M. Varma, Character

recognition in natural images, in Proceedings of the

International Conference on Computer Vision Theory and

Applications, Lisbon, Portugal, February 2009. 4

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THANK YOU

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