DocumentCode :
2474232
Title :
A novel form structure extraction method using strip projection
Author :
Chen, Jim-Lin ; Lee, Hsi-Jian
Author_Institution :
Dept. of Comput. Sci. & Inf. Eng., Nat. Chiao Tung Univ., Hsinchu, Taiwan
Volume :
3
fYear :
1996
fDate :
25-29 Aug 1996
Firstpage :
823
Abstract :
A form processing system aims to extract meaningful data from a form document for office automation. To locate the data, we have to extract and understand the form structure. In this paper, a strip projection method is presented for extracting form structure. We first segment the input form image uniformly into vertical and horizontal strips. Since most lines in a form are vertical and horizontal lines, we project the image in each vertical strip horizontally and in each horizontal strip vertically. The peak positions in the projection profiles denote the possible existence of lines in the form image. Next we trace the lines started from the possible line positions in the source image. After all lines are extracted, redundant lines are removed by a line verification algorithm and broken lines are linked by a line merging algorithm. This proposed method can reduce much computation time than other methods such as Hough transformation and line detection and approximation algorithm. Experimental results demonstrate that the proposed method is very effective
Keywords :
computational complexity; document image processing; feature extraction; image segmentation; office automation; redundancy; broken line linkage; form processing system; form structure extraction method; line merging algorithm; line verification algorithm; meaningful data extraction; office automation; redundant line removal; strip projection; Approximation algorithms; Automation; Binary trees; Character recognition; Computer science; Data mining; Image segmentation; Intelligent systems; Strips; Tail;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition, 1996., Proceedings of the 13th International Conference on
Conference_Location :
Vienna
ISSN :
1051-4651
Print_ISBN :
0-8186-7282-X
Type :
conf
DOI :
10.1109/ICPR.1996.547283
Filename :
547283
Link To Document :
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