RECOGNITION OF HANDWRITTEN DEVANAGARI NUMERAL STRING USING A MULTI-LAYER PERCEPTRON NEURAL NETWORK

Suraj Regmi
2017
BSc.CSIT
Semester 7
Downloads 4

Handwritten Recognition is the process of text extraction from images of handwritten text. Devanagari numeral string is the collection of devanagari digits forming a number. In this project handwritten Devanagari numeral string recognition is done using Multilayer Perceptron Neural Network (MLP). Handwriting Recognizer a system that locates and recognizes devanagari numeral strings written in a white paper. The classifier used to recognize the Devanagari digit is Multi-Layer Perceptron Neural Network that has 1028(32*32) input nodes, 300 hidden nodes and 10 output nodes. First, the Neural Network is trained with 1700 data sets of each digit (0-9). The images of handwritten text is preprocessed and then fed to neural networks for recognition. The obtained result gives 96.5 % accuracy with a learning rate of 0.3.

Multi-layer Perceptron Neural Network
Back Propagation Algorithm
Nepali digits recognition
devanagari digit recognition
handwritten digit recognition

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