Title :
Detecting Text in Videos Using Fuzzy Clustering Ensembles
Author :
Gllavata, Julinda ; Qeli, Ermir ; Freisleben, Bernd
Author_Institution :
Dept. of Math. & Comput. Sci., Marburg Univ.
Abstract :
Detection and localization of text in videos is an important task towards enabling automatic content-based retrieval of digital video databases. However, since text is often displayed against a complex background, its detection is a challenging problem. In this paper, a novel approach based on fuzzy cluster ensemble techniques to solve this problem is presented. The advantage of this approach is that the fuzzy clustering ensemble allows the incremental inclusion of temporal information regarding the appearance of static text in videos. Comparative experimental results for a test set of 10.92 minutes of video sequences have shown the very good performance of the proposed approach with an overall recall of 92.04% and a precision of 96.71%
Keywords :
image sequences; text analysis; video databases; fuzzy cluster ensemble technique; incremental inclusion; text detection; video sequence; Clustering algorithms; Computer science; Data mining; Feature extraction; Information retrieval; Layout; Mathematics; Neural networks; Testing; Video sequences;
Conference_Titel :
Multimedia, 2006. ISM'06. Eighth IEEE International Symposium on
Conference_Location :
San Diego, CA
Print_ISBN :
0-7695-2746-9
DOI :
10.1109/ISM.2006.60