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A GA Based approach for selection of local features for recognition of handwritten Bangla numerals
In the current work we have developed a two-pass approach where the first pass classifier performs a coarse classification, based on some global features of the input pattern by restricting the possibility of classification decisions within a group of classes, smaller than the number of classes considered initially.
Design of a novel convex hull based feature set for recognition of isolated handwritten Roman numerals
In this work, 25 features are extracted based on different bays attributes of the convex hull of the digit patterns.
Recognition of Handwritten Bangla Basic Characters and Digits using Convex Hull based Feature Set
The current research aims to evaluate the performance of the convex hull based feature set, i. e. 125 features in all computed over different bays attributes of the convex hull of a pattern, for effective recognition of isolated handwritten Bangla basic characters and digits.
