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CHAIN CODE PROCESSING FOR HANDWRITTEN WORD RECOGNITION

Authors: SHAKUNTHALA B S; C S PILLAI;

CHAIN CODE PROCESSING FOR HANDWRITTEN WORD RECOGNITION

Abstract

Contour representations are well suited for representing handwritten word images. The storage is lossless and the processing time required is a relatively small. While chain code encoding of contours has been favored by researchers in the area of handwriting recognition the representation does have some drawbacks. Firstly, a simple shift of a single pixel can cause a break in the contour, or introduce a point that does not adhere to the property that the contour must be a single pixel wide at all points of the contour. Such an event can occur during slant correction or noise removal. the speed efficiency of a character recognizer that uses chain code representation, For lexicons of size 1000, the time consumed by the chain code based preprocessing and feature extraction routines is less than 10% of the total time.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
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