DocumentCode
1776553
Title
Extraction of key frames from video using discrete cosine transform
Author
Thepade, Sudeep D. ; Tonge, Ashvini A.
Author_Institution
Dept. of Comput. Eng., Pimpri Chinchwad Coll. of Eng., Pune, India
fYear
2014
fDate
10-11 July 2014
Firstpage
1294
Lastpage
1297
Abstract
With the development of multimedia data types and available bandwidth there is huge demand of video retrieval systems as users shift from text based retrieval systems to content based retrieval systems (CBVRS). Selection of extracted features play an important role in content based video retrieval, regardless of video attributes under consideration. Good features selection also allows the time, space and cost saving in the retrieval process. This leads to the interest of selecting only those features that can be extracted from video data and used for indexing and retrieval along with similarity measurement methods. There are certain issues like video store, search, index and retrieve as a trend in area of content based video retrieval systems. In this paper, we have proposed a method. In this paper fractional discrete cosine transform coefficients are used to extract key frames which eventually save space and time with better completeness in the retrieval process.
Keywords
content-based retrieval; discrete cosine transforms; feature extraction; video retrieval; CBVRS; content based retrieval system; discrete cosine transform; feature extraction; feature selection; key frame extraction; multimedia data types; retrieval process; similarity measurement methods; text based retrieval system; video retrieval system; Discrete cosine transforms; Feature extraction; Indexing; Instruments; Streaming media; CBVR; DCT; Key frame; consecutive frame differencs;
fLanguage
English
Publisher
ieee
Conference_Titel
Control, Instrumentation, Communication and Computational Technologies (ICCICCT), 2014 International Conference on
Conference_Location
Kanyakumari
Print_ISBN
978-1-4799-4191-9
Type
conf
DOI
10.1109/ICCICCT.2014.6993160
Filename
6993160
Link To Document