Proceedings ArticleDOI
Application Of Mathematical Morphology To Handwritten ZIP Code Recognition
Andrew M. Gillies,Paul D. Gader,Michael P. Whalen,Brian T. Mitchell +3 more
- Vol. 1199, pp 380-389
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TLDR
The morphological techniques used for preprocessing address block images, locating address block lines, splitting touching characters, and identifying handwritten numerals combine mathematical morphology, hierarchical matching of object models to symbolic image representations, and a strategy of propagating multiple hypotheses.Abstract:
This paper describes applications of mathematical morphology to a system for recognizing handwritten ZIP Codes. It discusses morphological techniques used for preprocessing address block images, locating address block lines, splitting touching characters, and identifying handwritten numerals. These techniques combine mathematical morphology, hierarchical matching of object models to symbolic image representations, and a strategy of propagating multiple hypotheses. The various submodules of the system have been trained on over two thousand real address block images and tested on one thousand representative images. On the one thousand test images, the system correctly located 82.5 percent, correctly identified 45.6 percent, and incorrectly classified only 0.8% of the ZIP Codes. This system performance level could lead to a significant cost savings in mail piece sorting.read more
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A segmentation-free approach to text recognition with application to Arabic text
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Journal ArticleDOI
Segmentation-recognition algorithm for zip code field recognition
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TL;DR: The algorithm consists of an initial character segmentation algorithm and a connected-numeral splitting algorithm that is integrated with a statistical classifier to form a segmentation-recognition algorithm to resolve the ambiguity of connected numeral splitting.
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Using spatial relationships as features in object recognition
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Book ChapterDOI
Applying iconic processing in machine vision
TL;DR: This chapter presents an iconic approach using morphological image processing as a tool for analyzing images to recover 2-D information and shows that the iconic approach offers features that could simplify many tasks in machine vision systems.
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