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Content Provider | IET Digital Library |
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Author | Vo, Quang Nhat Kim, Soo Hyung Yang, Hyung Jeong Lee, Guee Sang |
Abstract | Line detection in handwritten documents is an important problem for processing of scanned documents. While existing approaches mainly use hand-designed features or heuristic rules to estimate the location of text lines, the authors present a novel approach that trains a fully convolutional network (FCN) to predict text line structure in document images. A rough estimation of text line, or a line map, is obtained by using FCN, from which text strings that pass through characters in each text line are constructed. Finally, the touching characters should be separated and assigned to different text lines to complete the segmentation, for which line adjacency graph is used. Experimental results on ICDAR2013 Handwritten Segmentation Contest data set show high performance together with the robustness of the system with different types of languages and multi-skewed text lines. |
Starting Page | 438 |
Ending Page | 446 |
Page Count | 9 |
ISSN | 17519659 |
Volume Number | 12 |
e-ISSN | 17519667 |
Issue Number | Issue 3, Mar (2018) |
Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/iet-ipr/12/3 |
Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2017.0083 |
Journal | IET Image Processing |
Publisher Date | 2017-11-03 |
Access Restriction | Open |
Rights Holder | © The Institution of Engineering and Technology |
Subject Keyword | Combinatorial Mathematics Computer Vision And Image Processing Technique Document Image Processing Document Processing Technique Edge Detection FCN Fully Convolutional Network Graph Theory Hand-designed Feature Handwritten Character Recognition Handwritten Document Image Heuristic Rules ICDAR2013 Handwritten Segmentation Contest Data Set Image Recognition Image Segmentation Line Adjacency Graph Line Detection Line Map Multiskewed Text Line Neural Computing Technique Neural Nets Scanned Document Processing Text Detection Text Line Location Estimation Text Line Segmentation Text Line Structure Prediction Text Strings Touching Characters |
Content Type | Text |
Resource Type | Article |
Subject | Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software |
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