Generating Ground Truthed Dataset of Chart Images: Automatic or Semi-automatic?

Authors:
Weihua Huang;Chew Lim Tan;Jiuzhou Zhao
Affiliations:
School of Computing, National University of Singapore, Singapore 117543;School of Computing, National University of Singapore, Singapore 117543;School of Computing, National University of Singapore, Singapore 117543
Venue:
Graphics Recognition. Recent Advances and New Opportunities
Year:
2008

Citing 10
Cited 2

Digital image processing (2nd ed.)

Digital image processing (2nd ed.)
Twenty Years of Document Image Analysis in PAMI

IEEE Transactions on Pattern Analysis and Machine Intelligence
Numerical Recipes in C++: the art of scientific computing

Numerical Recipes in C++: the art of scientific computing
A Course in Simulation

A Course in Simulation
Automatic Table Ground Truth Generation and a Background-Analysis-Based Table Structure Extraction Method

ICDAR '01 Proceedings of the Sixth International Conference on Document Analysis and Recognition
A Line Drawings Degradation Model for Performance Characterization

ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 2
Document Image Ground Truth Generation from Electronic Text

ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 2 - Volume 02
PerfectDoc: A Ground Truthing Environment for Complex Documents

ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
A Ground-Truthed Mathematical Character and Symbol Image Database

ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
Semi-automatic ground truth generation for chart image recognition

DAS'06 Proceedings of the 7th international conference on Document Analysis Systems

An evaluation framework for stereo-based driver assistance

Proceedings of the 15th international conference on Theoretical Foundations of Computer Vision: outdoor and large-scale real-world scene analysis
A semi-automatic groundtruthing framework for performance evaluation of symbol recognition and spotting systems

GREC'11 Proceedings of the 9th international conference on Graphics Recognition: new trends and challenges

Quantified Score

Hi-index	0.00

Visualization

Abstract

Ground truthing tools mainly fall into two categories: automatic and semi-automatic. In this paper, we first discuss the pros and cons of the two approaches. We then report our own work on designing and implementing systems for generating a chart image dataset and multi-level ground truth data. Both semi-automatic and automatic approaches were adopted, resulting in two independent systems. The dataset as well as the ground truth data are publicly available so that other researchers can access them for evaluating and comparing performances of different systems.