Off-line hand written input based identity determination using multi kernel feature combination

• Novel MKL formulation for multiple feature based identity determination.
• GA algorithm based optimization in MKL for nearest neighbor classification.
• Novel feature representations for handwritten data.

The paper presents a novel framework for the application of multiple features for handwritten data based identity recognition. Different types of features characterise different facets of the handwriting. We have designed a scheme for multiple feature based identity establishment using multi-kernel learning. A new formulation for multi-kernel learning using genetic algorithm has been presented. The efficacy of the framework using individual and combination of features is demonstrated for Devanagari script input.