Similar looking Gujarati printed character recognition using Locality Preserving Projection and artificial neural networks
Autor: | Suman K. Mitra, Gitam Shikkenawis, Mandar S. Chaudhary, Mukesh M. Goswami |
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Rok vydání: | 2012 |
Předmět: |
Artificial neural network
Computer science business.industry Locality Feature extraction Pattern recognition Optical character recognition computer.software_genre language.human_language Character (mathematics) language Gujarati Artificial intelligence business Projection (set theory) computer Curse of dimensionality |
Zdroj: | 2012 Third International Conference on Emerging Applications of Information Technology. |
DOI: | 10.1109/eait.2012.6407884 |
Popis: | 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. |
Databáze: | OpenAIRE |
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