Paper Info
Title
An automatic performance evaluation protocol for video text detection algorithms
Abstract
Text presented in videos provides important supplemental information for video indexing and retrieval. Many efforts have been made for text detection in videos. However, there is still a lack of performance evaluation protocols for video text detection. In this paper, we propose an objective and comprehensive performance evaluation protocol for video text detection algorithms. The protocol includes a positive set and a negative set of indices at the textbox level, which evaluate the detection quality in terms of both location accuracy and fragmentation of the detected textboxes. In the protocol, we assign a detection difficulty (DD) level to each ground truth textbox. The performance indices can then be normalized with respect to the textbox DD level and are therefore tolerant to different ground-truth difficulties to a certain degree. We also assign a detectability index (DI) value to each ground-truth textbox. The overall detection rate is the DI-weighted average of the detection qualities of all ground-truth textboxes, which makes the detection rate more accurate to reveal the real performance. The automatic performance evaluation scheme has been applied to performance evaluation of a text detection approach to determine the best thresholds that can yield the best detection results. The protocol has also been employed to compare the performances of several text detection systems. Hence, we believe that the proposed protocol can be used to compare the performance of different video/image text detection algorithms/systems and can even help improve, select, and design new text detection methods.
Year
DOI
Venue
2004
10.1109/TCSVT.2004.825538
IEEE Trans. Circuits Syst. Video Techn.
Keywords
Field
DocType
video text detection.,detection quality,automatic performance evaluation protocol,detection result,detection difficulty,video text detection algorithm,index terms—performance evaluation,text detection approach,text detection system,image text detection algorithm,new text detection method,detection rate,overall detection rate,text detection,image analysis,data mining,information retrieval,information analysis,ground truth,indexing,text analysis,indexing terms,helium,image retrieval,indexation,performance indicator,protocols,algorithm design and analysis
Data mining,Normalization (statistics),Computer science,Search engine indexing,Image retrieval,Artificial intelligence,Computer vision,Object detection,Text mining,Pattern recognition,Algorithm,Ground truth,Content based retrieval,Text detection
Journal
Volume
Issue
ISSN
14
4
1051-8215
Citations 
PageRank 
References 
48
2.88
19
Authors
3
Name
Order
Citations
PageRank
Xian-Sheng Hua16566328.17
Liu Wenyin22531215.13
Hong-Jiang ZHANG3173781393.22