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Proceedings Paper

Automatic line detection in document images using recursive morphological transforms
Author(s): Bin Kong; Su S. Chen; Robert M. Haralick; Ihsin T. Phillips
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Paper Abstract

In this paper, we describe a system that detects lines of various types, e.g., solid lines and dotted lines, on document images. The main techniques are based on the recursive morphological transforms, namely the recursive opening and closing transforms. The advantages of the transforms are that they can perform binary opening and closing with any sized structuring element simultaneously in constant time per pixel, and that they offer a solution to morphological image analysis problems where the sizes of the structuring elements have to be determined after the examination of the image itself. The system is evaluated on about 1,200 totally ground-truthed IRS tax form images of different qualities. The line detection output is compared with a set of hand-drawn groundtruth lines. The statistics like the number and rate of correct detection, miss detection, and false alarm are calculated. The performance of 32 algorithms for solid line detection are compared to find the best one. The optimal algorithm tuning parameter settings could be estimated on the fly using a regression tree.

Paper Details

Date Published: 30 March 1995
PDF: 12 pages
Proc. SPIE 2422, Document Recognition II, (30 March 1995); doi: 10.1117/12.205818
Show Author Affiliations
Bin Kong, Univ. of Washington (United States)
Su S. Chen, Univ. of Washington (United States)
Robert M. Haralick, Univ. of Washington (United States)
Ihsin T. Phillips, Seattle Univ. (United States)


Published in SPIE Proceedings Vol. 2422:
Document Recognition II
Luc M. Vincent; Henry S. Baird, Editor(s)

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