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Journal ArticleDOI

Recognition of handwritten numerical characters for automatic letter sorting

H. Genchi, +3 more
- Vol. 56, Iss: 8, pp 1292-1301
TLDR
A prototype of a postal code number reader capable of recognizing handwritten arabic numerals has been developed and tested successfully and the use of sequential recognition logic helps reduce the capacity of core memory required to obtain the desired high rate of recognition.
Abstract
A prototype of a postal code number reader capable of recognizing handwritten arabic numerals has been developed and tested successfully. Recognition of handwritten arabic numerals requires sufficient system flexibility to cope with both unlimited variations in character shape and a large number of writing instruments. This flexibility has been achieved by combining the use of a stored recognition table and a hardware microprogram. The recognition logic obtained by computer simulation is immediately stored in the core memory as a table. The numerals are recognized by extracting a sequence of the geometrical features in horizontal zones of the character after normalization of the height of the character and the width of the strokes. The use of sequential recognition logic helps reduce the capacity of core memory required to obtain the desired high rate of recognition. The correct recognition rate of a single digit for a large sample of letters averaged 95 percent. For a three-digit sorting with 13 stackers the sorter incorrectly recognized approximately 0.1 percent, a rate of error consistent with manual sorting.

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Citations
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Journal ArticleDOI

A distance measure between attributed relational graphs for pattern recognition

TL;DR: A method to determine a distance measure between two nonhierarchical attributed relational graphs is presented and an application of this distance measure to the recognition of lower case handwritten English characters is presented.
Journal ArticleDOI

Historical review of OCR research and development

TL;DR: Both template matching and structure analysis approaches to R&D are considered and it is noted that the two approaches are coming closer and tending to merge.

Picture processing by computer

TL;DR: The field of picture processing by computer is reviewed from a technique-oriented standpoint and the processing of given pictures (as opposed to computer-synthesized pictures) is considered.
Journal ArticleDOI

Automatic recognition of handprinted characters—The state of the art

TL;DR: Recognition algorithms, data bases, character models, and handprint standards are examined and Achievements in the recognition of handprinted numerals, alphanumerics, Fortran, and Katakana characters are analyzed and compared.
Journal ArticleDOI

Some Parallel Thinning Algorithms for Digital Pictures

TL;DR: It is proved that several algorithms which perform a thinning transformation when applied to the picture in parallel do not change the connectivity properties of the picture.
References
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Journal ArticleDOI

Pattern Detection and Recognition

TL;DR: Two types of pattern-processing problems are discussed in this paper and recognition and detection have been successfully carried out on an IBM 704 computer programmed to simulate a spatial computer (a stored-program machine comprised of a master control unit directing a network of logical modules).
Journal ArticleDOI

The recognition of handwritten numerals by contour analysis

TL;DR: A character recognition system has been developed for the recognition of handwritten numerals using a logically controlled cathode ray tube scanner to generate basic measurements that characterize significant features of the numeral shapes.
Proceedings ArticleDOI

Recognition of sloppy, hand-printed characters

TL;DR: A pattern recognition scheme particularly intended to handle noisy and highly distorted data, which has been applied to hand-printed English capitals but is evidently general.
Journal ArticleDOI

Machine recognition of hand printing

TL;DR: A generalized method developed which is based on a hierarchical sequence of classification stages, using the insignificance index, resulted in a reduction of the error rate over that of the unmodified correlation-based identification by a factor of 2.5.