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- W2405441411 abstract "In the field of Optical Character Recognition (OCR), zoning is used to extract topological information from patterns. In this paper we propose Zone based features for recognition of the mixer of Handwritten and Printed Kannada Digits. A digit image is divided into 64 zones and pixel density is computed for each zone. This procedure is sequentially repeated for entire zone. Finally 64 features are extracted for classification and recognition. There could be some zone column/row having empty foreground pixels. Hence the feature value of such particular zone column/row in the feature vector is zero. The KNN and SVM classifiers are used to classify the mixed handwritten and printed Kannada digits. We have obtained 97.32% & 98.30% recognition rate for mixed handwritten and printed Kannada digits by using KNN and SVM classifiers respectively." @default.
- W2405441411 created "2016-06-24" @default.
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- W2405441411 date "2011-01-01" @default.
- W2405441411 modified "2023-09-27" @default.
- W2405441411 title "Zone Based Features for Handwritten and Printed Mixed Kannada Digits Recognition" @default.
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