On-Line Digit Recognition Using Off-Line Features
نویسندگان
چکیده
This paper describes a classification method for on-line handwritten digits based on off-line image representations. The goal is to use image-based features to improve classifier accuracy for on-line handwritten input. In this paper we describe an initial framework that can be used to achieve this goal. This framework for handwritten digit classification is based on genetic programming (GP). Several issues in preprocessing, transformation of data from on-line to off-line domains and feature extraction are described. Results are reported on the UNIPEN digit dataset.
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