NDLI: Distance features for neural network-based recognition of handwritten characters

Content Provider	Springer Nature Link
Author	Oh, Il Seok Suen, Ching Y.
Copyright Year	1998
Abstract	Features play an important role in OCR systems. In this paper, we propose two new features which are based on distance information. In the first feature (called DT, Distance Transformation), each white pixel has a distance value to the nearest black pixel. The second feature is called DDD (Directional Distance Distribution) which contains rich information encoding both the black/white and directional distance distributions. A new concept of map tiling is introduced and applied to the DDD feature to improve its discriminative power. For an objective evaluation and comparison of the proposed and conventional features, three distinct sets of characters (i.e., numerals, English capital letters, and Hangul initial sounds) have been tested using standard databases. Based on the results, three propositions can be derived to confirm the superiority of both the DDD feature and the map tilings.
Starting Page	73
Ending Page	88
Page Count	16
File Format	PDF
ISSN	14332833
Journal	International Journal of Document Analysis and Recognition (IJDAR)
Volume Number	1
Issue Number	2
Language	English
Publisher	Springer-Verlag
Publisher Date	1998-07-01
Publisher Place	Berlin Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Content Type	Text
Resource Type	Article
Subject	Computer Science Applications Computer Vision and Pattern Recognition Software

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Distance features for neural network-based recognition of handwritten characters