Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/41047
Title: Semi-automatic ground truth generation for chart image recognition
Authors: Yang, L.
Huang, W. 
Tan, C.L. 
Issue Date: 2006
Citation: Yang, L.,Huang, W.,Tan, C.L. (2006). Semi-automatic ground truth generation for chart image recognition. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 3872 LNCS : 324-335. ScholarBank@NUS Repository.
Abstract: While research on scientific chart recognition is being carried out, there is no suitable standard that can be used to evaluate the overall performance of the chart recognition results. In this paper, a system for semi-automatic chart ground truth generation is introduced. Using the system, the user is able to extract multiple levels of ground truth data. The role of the user is to perform verification and correction and to input values where necessary. The system carries out automatic tasks such as text blocks detection and line detection etc. It can effectively reduce the time to generate ground truth data, comparing to full manual processing. We experimented the system using 115 images. The images and ground truth data generated are available to the public. © Springer-Verlag Berlin Heidelberg 2006.
Source Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
URI: http://scholarbank.nus.edu.sg/handle/10635/41047
ISBN: 3540321403
ISSN: 03029743
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.