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IPM
30
YEARS OLD

“School of Cognitive Sciences”

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Paper   IPM / Cognitive Sciences / 8747
School of Cognitive Sciences
  Title:   Optical character recognition motivated by Primate Visual System
  Author(s): 
1.  A. Borji
2.  M. Hamidi
  Status:   Published
  Journal: Neural Network World
  No.:  5
  Vol.:  16
  Year:  2007
  Pages:   433-445
  Supported by:  IPM
  Abstract:
A visual nervous system inspired approach to optical character recognition is proposed in this paper with the hope to touch human performance in a limited extent. Particularly, the application of features motivated by the hierarchical structure of the visual ventral stream for recognition of both English and Persian handwritten digits is investigated. Features are derived by combining position and scale invariant edge detectors in a hierarchy over neighboring positions and multiple orientations. The extracted features are then used to train and test a classifier. We examine three types of classifiers: ANN, SVM and kNN to show that features are not dependent on a specific classifier which is in support of these features. The evaluation of the proposed method over standard Persian and English handwritten digit datasets shows high recognition rates of 99.63

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