Similar looking Gujarati printed character recognition using Locality Preserving Projection and artificial neural networks

An attempt has been made to recognize similar looking printed Gujarati characters. It has been assumed that similar looking character recognition is the main challenge for an OCR to work efficiently. The dimensionality of the character images is drastically and very efficiently reduced and presented by only a few significant coefficients. A new mechanism called ESLPP is introduced for the same. Coefficients extracted using ESLPP which explores the natural grouping, preserves the local structure of the data and finds the essential data manifold structure, are then fed to the Neural Network as features. Six datasets each consisting of two or more similar looking characters are used for experimentation. The recognition accuracy in all the experiments is found to be very satisfactory.