Computer recognition of handwritten hebrew characters

Itshak Dinstein

doi:10.1016/0165-1684(81)90066-9

Computer recognition of handwritten hebrew characters

Itshak Dinstein

Department of Electrical & Computer Engineering

Research output: Contribution to journal › Article › peer-review

Abstract

Preliminary results of experiments with computer recognition of handwritten Hebrew characters are presented. The features used for the classification were the number of line crossings along some specified intersections, and the relative lengths of horizontal and vertical segments. Characters were clustered, first, according to some geometrical properties. Test characters within each cluster were then classified considering only those characters of the training set which were assigned to the same cluster. A min-Max decision rule yielded 90.9 percent of correct classification.

Original language	English
Pages (from-to)	73-77
Number of pages	5
Journal	Signal Processing
Volume	3
Issue number	1
DOIs	https://doi.org/10.1016/0165-1684(81)90066-9
State	Published - 1 Jan 1981

Keywords

Character recognition
classification
clustering

ASJC Scopus subject areas

Control and Systems Engineering
Software
Signal Processing
Computer Vision and Pattern Recognition
Electrical and Electronic Engineering

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10.1016/0165-1684(81)90066-9

Cite this

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title = "Computer recognition of handwritten hebrew characters",

abstract = "Preliminary results of experiments with computer recognition of handwritten Hebrew characters are presented. The features used for the classification were the number of line crossings along some specified intersections, and the relative lengths of horizontal and vertical segments. Characters were clustered, first, according to some geometrical properties. Test characters within each cluster were then classified considering only those characters of the training set which were assigned to the same cluster. A min-Max decision rule yielded 90.9 percent of correct classification.",

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AB - Preliminary results of experiments with computer recognition of handwritten Hebrew characters are presented. The features used for the classification were the number of line crossings along some specified intersections, and the relative lengths of horizontal and vertical segments. Characters were clustered, first, according to some geometrical properties. Test characters within each cluster were then classified considering only those characters of the training set which were assigned to the same cluster. A min-Max decision rule yielded 90.9 percent of correct classification.

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KW - classification

KW - clustering

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Computer recognition of handwritten hebrew characters

Abstract

Keywords

ASJC Scopus subject areas

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