A HSV-SILTP Based Shadow Suppression Approach for Moving Vehicle Extraction

Author

Yang Zhang ; Huazhong Xu ; Man Luo

Author_Institution

Sch. of Autom., Wuhan Univ. of Technol. Wuhan, Wuhan, China

fYear

2013

fDate

26-28 July 2013

Firstpage

846

Lastpage

851

Abstract

This paper introduces a real-time method to extract vehicles in road environment, and mainly includes four parts as follows: firstly, using Double Level background learning method to obtain a stable background image and get a rough vehicle area. Secondly, using HSV color space and texture characteristics of SILTP mixed constraint method to suppress the influence of shadow. Thirdly, using Energy Density Analysis to enhance the area-of-interest, and finally, showing some experimental results.

Keywords

automated highways; feature extraction; image colour analysis; image texture; learning (artificial intelligence); traffic engineering computing; video signal processing; HSV color space characteristics; HSV color texture characteristics; HSV-SILTP based shadow suppression approach; ITS; SILTP mixed constraint method; background image stability; double level background learning method; energy density analysis; intelligent transportation system; moving vehicle extraction; road environment; road traffic video monitoring; scale invariant local ternary pattern; Educational institutions; Image color analysis; Noise; Real-time systems; Roads; Streaming media; Vehicles; background learning; shadow suppressing; vehicle extrction;

fLanguage

English

Publisher

ieee

Conference_Titel

Image and Graphics (ICIG), 2013 Seventh International Conference on

Conference_Location

Qingdao

Type

conf

DOI

10.1109/ICIG.2013.172

Filename

6643789