[1]TAN Ting,LYU Shujing,LYU Yue.Form location and extraction based on graph representation and matching[J].CAAI Transactions on Intelligent Systems,2019,14(2):231-238.[doi:10.11992/tis.201709038]
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Form location and extraction based on graph representation and matching

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 14 Number of periods: 2019 2 Page number: 231-238 Column: 学术论文—机器学习 Public date: 2019-03-05
Title:
Form location and extraction based on graph representation and matching
Author(s):
TAN Ting1;  LYU Shujing2;  LYU Yue1; 2
1. Shanghai Key Laboratory of Multidimensional Information Processing, East China Normal University, Shanghai 200062, China;
2. ECNU-SRI Joint Lab for Pattern Analysis and Intelligent System, Shanghai Research Institute of China Post, Shanghai 200062, China
Keywords:
image segmentation; form extraction; form location; graph representation; graph matching; isomorphic graph; express package sorting
CLC:
TP751.1
DOI:
10.11992/tis.201709038
Abstract:
To obtain information of a user’s interested region on express package images of different types, resolutions, and directions, a form location and extraction method based on graph representation and matching is proposed in this paper. A reference form is needed in this method. First, key regions such as the existing printed patterns or characters in the reference form are chosen as nodes to build the reference graph. Second, graph representation is conducted on the form to be processed based on the candidate key region derived from image segmentation. Then, the similarity between the reference form and the candidate form is calculated according to attributes of the graph. Finally, the isomorphic graph with the maximum similarity is chosen as the optimal matching of the reference form and graph, and the position mapping of the isomorphic graph and the reference form and test image is established to locate the form. The experimental datasets in this paper originate from express package images collected in practical scenarios. Experimental results indicate that the proposed algorithm has good performance on express form images. Especially, good robustness is achieved for rotated, illuminated, and partially shaded images.
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