Automatic line detection in document images using recursive morphological transforms

Bin Kong; Su S. Chen; Robert M. Haralick; Ihsin T. Phillips

doi:10.1117/12.205818

30 March 1995 Automatic line detection in document images using recursive morphological transforms

Bin Kong, Su S. Chen, Robert M. Haralick, Ihsin T. Phillips

Proceedings Volume 2422, Document Recognition II; (1995) https://doi.org/10.1117/12.205818
Event: IS&T/SPIE's Symposium on Electronic Imaging: Science and Technology, 1995, San Jose, CA, United States

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.

Citation Download Citation

Bin Kong, Su S. Chen, Robert M. Haralick, and Ihsin T. Phillips "Automatic line detection in document images using recursive morphological transforms", Proc. SPIE 2422, Document Recognition II, (30 March 1995); https://doi.org/10.1117/12.205818

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