Abstract
Character recognition in natural images has been a subject of study by scholars since the 1970s. Various feature extraction and classification techniques have been proposed, each with a certain degree of accuracy. In this article, we describe an approach to performing such classification on Kannada characters of handwritten origin or those present in natural images, using histogram of oriented gradients descriptors, for feature extraction from character images, and employing a machine learning model (neural networks or support vector machines) for final classification. Our approach gives excellent classification accuracies on the handwritten Kannada characters taken from the Chars74k dataset, compared to previous work.
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Yadav, D.P., Kumar, M. (2018). Kannada Character Recognition in Images Using Histogram of Oriented Gradients and Machine Learning. In: Chaudhuri, B., Kankanhalli, M., Raman, B. (eds) Proceedings of 2nd International Conference on Computer Vision & Image Processing . Advances in Intelligent Systems and Computing, vol 704. Springer, Singapore. https://doi.org/10.1007/978-981-10-7898-9_22
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DOI: https://doi.org/10.1007/978-981-10-7898-9_22
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