DocumentCode
3341699
Title
An Improved Video Compression Algorithm for Lane Surveillance
Author
Zhao Shu-long ; You Zhi-Sheng ; Lan Shi-yong ; Zhou Xin
Author_Institution
Sichuan Univ., Chengdu
fYear
2007
fDate
22-24 Aug. 2007
Firstpage
224
Lastpage
229
Abstract
In order to process huge volume of data efficiently in video surveillance system, it is very necessary and important to find out high efficient video retrieval techniques and advanced video compression techniques. This paper presents an improved video compression algorithm for lane supervision, which considers the implementation of video retrieval at the stage of video compression. This improved video compression algorithm combines the following three parts: shot segmentation based on detection of moving vehicle; key frame extraction based on vehicle-license- plate locating; video compression in which the I frame, B frame and P frame is decided by the former two steps. Experimental results show that the algorithm presented in this paper not only increases the compression ratio, but also improves the quality of the video reverting from compressed video and improves the efficiency and performance of the later video retrieval.
Keywords
data compression; feature extraction; image motion analysis; image segmentation; video coding; video retrieval; video surveillance; key frame extraction; lane surveillance; moving vehicle detection; shot segmentation; vehicle-license-plate locating; video compression algorithm; video retrieval techniques; video surveillance system; Computer graphics; Data mining; Educational institutions; Image coding; Image segmentation; Information retrieval; Local area networks; Vehicle detection; Video compression; Video surveillance; Key Frame Extraction; Segmentation; Shot; Vehicle-licenseplate Locating; Video Compression;
fLanguage
English
Publisher
ieee
Conference_Titel
Image and Graphics, 2007. ICIG 2007. Fourth International Conference on
Conference_Location
Sichuan
Print_ISBN
0-7695-2929-1
Type
conf
DOI
10.1109/ICIG.2007.75
Filename
4297087
Link To Document