V. N. Manjunath Aradhya

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Character recognition lies at the core of the discipline of pattern recognition where the aim is to represent a sequence of characters taken from an alphabet [Kasturi, R., Gorman, L.O., Govindaraju, V., 2002. Document image analysis: a primer. Sadhana 27 (Part 1), 3–22]. Though many kinds of features have been developed and their test performances on(More)
In this paper, recognition system for totally unconstrained handwritten characters for south Indian language of Kannada is proposed. The proposed feature extraction technique is based on Fourier Transform and well known Principal Component Analysis (PCA). The system trains the appropriate frequency band images followed by PCA feature extraction scheme. For(More)
Separating text lines in handwritten documents remains a challenge because the text lines are often varying skewed and curved. In this paper, we propose a novel method for text line segmentation of unconstrained handwritten Kannada script. The proposed method consists of two phases. In the first phase, mathematical morphology technique is used to bridge the(More)
Nowadays’ most of the software products are developed by using existing versions or features in order to reduce the delivery time of software product, to improve the productivity and quality and to reduce the development effort. Software reuse has been a solution factor to acquire the existing knowledge from software repository. To extract existing(More)
Handwritten character recognition is a difficult problem due to the great variations on writing styles, different size and orientation angle of the characters. In this paper, we propose an unconstrained handwritten Kannada character recognition based on the ridgelet transforms. Ridglets are a powerful instrument in catching and representing mono-dimensional(More)