NDLI: Cursive handwriting recognition using the Hough transform and a neural network

Content Provider	IEEE Xplore Digital Library
Author	Ruiz-Pinales, J. Lecolinet, E.
Copyright Year	2000
Description	Author affiliation: Dept. of Comput. Sci. & Networks, Ecole Nat. Superieure des Telecommun., Paris, France (Ruiz-Pinales, J.)
Abstract	In this paper, we present a system for the recognition of cursive handwriting that utilizes the Hough transform and a neural network. The Hough transform is a line detection technique which has the ability of tolerating deformation, disconnections and noise. Instead of searching for linear strokes in the image, we compute global directional information at each pixel of the image. This information is stored into several feature maps. Thus we avoid assigning to each pixel a single orientation in order to preserve useful information. Each feature map is then processed by zones in order to estimate the local orientation of the strokes. Finally, we recognize the image by means of a neural network classifier. We have tested the system for the recognition of segmented cursive characters, cursive words and the first letter of cursive words. The results obtained are encouraging and compare well with respect to other results.
Starting Page	231
Ending Page	234
File Size	386369
Page Count	4
File Format	PDF
ISBN	0769507506
ISSN	10514651
DOI	10.1109/ICPR.2000.906055
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2000-09-03
Publisher Place	Spain
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Handwriting recognition Neural networks Feature extraction Image recognition Character recognition Statistical distributions Computer science Pixel System testing Image segmentation
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition

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