Paper Info
Title
Video OCR: indexing digital new libraries by recognition of superimposed captions
Abstract
The automatic extraction and recognition of news captions and annotations can be of great help locating topics of interest in digital news video libraries. To achieve this goal, we present a technique, called Video OCR (Optical Character Reader), which detects, extracts, and reads text areas in digital video data. In this paper, we address problems, describe the method by which Video OCR operates, and suggest applications for its use in digital news archives. To solve two problems of character recognition for videos, low-resolution characters and extremely complex backgrounds, we apply an interpolation filter, multiframe integration and character extraction filters. Character segmentation is performed by a recognition-based segmentation method, and intermediate character recognition results are used to improve the segmentation. We also include a method for locating text areas using text-like properties and the use of a language-based postprocessing technique to increase word recognition rates. The overall recognition results are satisfactory for use in news indexing. Performing Video OCR on news video and combining its results with other video understanding techniques will improve the overall understanding of the news video content.
Year
DOI
Venue
1999
10.1007/s005300050140
Multimedia Syst.
Keywords
Field
DocType
Key words:Digital video library – Caption – Index – OCR – Image enhancement
Computer vision,Intelligent character recognition,Segmentation,Computer science,Word recognition,Search engine indexing,Video tracking,Optical reader,Artificial intelligence,Multimedia,Automatic indexing,Intelligent word recognition
Journal
Volume
Issue
ISSN
7
5
0942-4962
Citations 
PageRank 
References 
104
9.15
12
Authors
5
Search Limit
100104
Name
Order
Citations
PageRank
Toshio Sato125834.34
Takeo Kanade2250734203.02
Ellen K. Hughes326033.52
Michael A. Smith4965159.32
Shin'ichi Satoh52093277.41