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.