Abstract:This paper provides an early attempt to train and retrieve handwritten Nandinagari characters using one of the latest techniques in visual feature detection. The data set consists of over 1600 handwritten Nandinagari characters of different fonts, size, rotation, translation and image formats. In the Learning phase, we subject them to an approach where their recognition is effective by first extracting their key interest points on the images which are invariant to Scale, rotation, translation, illumination and… Show more
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