A multi-objective approach towards cost effective isolated handwritten Bangla character and digit recognition

作者：

Highlights：

• Developed a cost effective approach towards handwritten character recognition system.

• A multi-objective region sampling methodology for isolated handwritten Bangla characters and digits recognition has been proposed.

• A non-dominated sorting harmony search algorithm based region sampling and a non-dominated sorting genetic algorithm based region sampling methodology have been developed.

• An AFS theory based fuzzy logic is utilized to develop a model for combining the pareto-optimal solutions from two multi-objective heuristics algorithms.

• Maximum recognition accuracies of 86.6478% and 98.23% have been achieved with 0.234% and 12.60% decrease in recognition cost for handwritten Bangla characters and digits respectively.

摘要

•Developed a cost effective approach towards handwritten character recognition system.•A multi-objective region sampling methodology for isolated handwritten Bangla characters and digits recognition has been proposed.•A non-dominated sorting harmony search algorithm based region sampling and a non-dominated sorting genetic algorithm based region sampling methodology have been developed.•An AFS theory based fuzzy logic is utilized to develop a model for combining the pareto-optimal solutions from two multi-objective heuristics algorithms.•Maximum recognition accuracies of 86.6478% and 98.23% have been achieved with 0.234% and 12.60% decrease in recognition cost for handwritten Bangla characters and digits respectively.

论文关键词：Feature set,Region sampling,Handwritten character recognition,Multi-objective evolutionary algorithm,Harmony search,NSGA-II,AFS theory

论文评审过程：Received 22 September 2015, Revised 22 March 2016, Accepted 13 April 2016, Available online 22 April 2016, Version of Record 26 May 2016.

论文官网地址：https://doi.org/10.1016/j.patcog.2016.04.010