Name
Abstract | ||
|---|---|---|
We propose a method to extract text information from video sequences. First the frequency of high horizontal energy in a video frame is examined to extract text blocks. Structural operations are then performed to remove the background so that the text can be extracted for later recognition. Experiments show that the method is efficient and effective for extracting text from various video documents. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1109/SSIRI.2008.26 | SSIRI |
Keywords | Field | DocType |
video signal processing,k-mean clustering,text information extraction,gray scale gradient (gdt),structural operation,later recognition,video images,text block,video image,connected-component,text information,discrete cosine transform (dct),image sequences,text extraction,text analysis,high horizontal energy,various video document,video frame,video sequence,computer science,indexing,k means clustering,discrete cosine transform,image reconstruction,connected component,frequency,k mean clustering,data mining,videoconference,information extraction,reliability engineering,pixel,information management | Iterative reconstruction,k-means clustering,Computer vision,Text mining,Pattern recognition,Computer science,Search engine indexing,Artificial intelligence,Connected component,Pixel,Videoconferencing,Text recognition | Conference |
ISBN | Citations | PageRank |
978-0-7695-3266-0 | 0 | 0.34 |
References | Authors | |
2 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shwu-huey Yen | 1 | 42 | 9.07 |
| Chun-Wei Wang | 2 | 11 | 1.97 |
| Jih Pin Yeh | 3 | 22 | 2.58 |
| Meng-Ju Lin | 4 | 8 | 1.70 |
| Hwei-jen Lin | 5 | 59 | 8.91 |