Handwritten Digit Recognition Using Slope Detail Features

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Provided by: International Journal of Computer Applications
Topic: Software
Format: PDF
In this paper, new features called Slope Detail (SD) features for handwritten digit recognition have been introduced. These features are based on shape analysis of the digit image and extract slant or slope information. They are effective in obtaining good recognition accuracies. When combined with commonly used features, Slope Detail (SD) features enhance the digit recognition accuracy. K- Nearest Neighbor (k-NN) and Support Vector Machine (SVM) algorithms have been used for classification purposes. The data sets used are the semeion data set and United States Postal Service (USPS) data set.
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