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Start Over Subject OCR

1. A new approach to signature verigication: digital data acquisition pen

Creator:
Rohlík, Ondřej, Mautner, Pavel, Matoušek, Václav, Kempf, Jürgen, and Weinzierl, Kurt
Format:
bez média and svazek
Type:
model:article and TEXT
Subject:
signature verification, person identification, character recognition, OCR, and HCI
Language:
English
Description:
This paper preseiits our experience with a completely new approach to handwritten text recognitiori. A brief description of a new type of input devices is followed by a more detailed explanation of recognition methods used. The results achieved are discussed and ideas ror further research are suggested.
Rights:
http://creativecommons.org/publicdomain/mark/1.0/ and policy:public

2. Optical character recognition motivated by Primate Visual System

Creator:
Borji, Ali and Hamidi, Mandana
Format:
bez média and svazek
Type:
model:article and TEXT
Subject:
Visual system, standard model, handwritten digit, nervous system, visual ventral stream, Persian, English, OCR, and HMAX
Language:
English
Description:
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% and 98.9%, respectively. A stability analysis is also performed to demonstrate the robustness of this method to orientation, scale, and translation distortions.
Rights:
http://creativecommons.org/publicdomain/mark/1.0/ and policy:public