Handwritten Word Recognition Using Multi-view Analysis

This paper brings a contribution to the problem of efficiently recognizing handwritten words from a limited size lexicon. For that, a multiple classifier system has been developed that analyzes the words from three different approximation levels, in order to get a computational approach inspired on the human reading process. For each approximation level a three-module architecture composed of a zoning mechanism (pseudo-segmenter), a feature extractor and a classifier is defined. The proposed application is the recognition of the Portuguese handwritten names of the months, for which a best recognition rate of 97.7% was obtained, using classifier combination.

• Type: Conference
• Year: 2009
• Where: CIARP
• Authors: José Josemar de Oliveira Jr., Cinthia Obladen de Almendra Freitas, João Marques de Carvalho, Robert Sabourin
• Keywords: Approximation Level, CIARP 2009, Different Approximation Levels, Handwritten Words, Image