Automatic text extraction from video for content-based annotation and retrieval

• Published in: Proceedings. Fourteenth International Conference on Pattern Recognition (Cat. No.98EX170) Vol. 1; pp. 618 - 620 vol.1
• Main Authors: Jae-Chang Shim, Dorai, C., Bolle, R.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 1998
• Subjects: Content based retrieval; Data mining; Digital images; Image databases; Image retrieval; Image segmentation; Information retrieval; Internet; Optical character recognition software; Robustness
• ISBN: 0818685123; 9780818685125
• ISSN: 1051-4651; 2831-7475
• DOI: 10.1109/ICPR.1998.711219

Efficient content-based retrieval of image and video databases is an important application due to rapid proliferation of digital video data on the Internet and corporate intranets. Text either embedded or superimposed within video frames is very useful for describing the contents of the frames, as it enables both keyword and free-text based search, automatic video logging, and video cataloging. We have developed a scheme for automatically extracting text from digital images and videos for content annotation and retrieval. We present our approach to robust text extraction from video frames, which can handle complex image backgrounds, deal with different font sizes, font styles, and font appearances such as normal and inverse video. Our algorithm results in segmented characters that can be directly processed by an OCR system to produce ASCII text. Results from our experiments with over 5000 frames obtained from twelve MPEG video streams demonstrate the good performance of our system in terms of text identification accuracy and computational efficiency.