شماره ركورد كنفرانس :
144
عنوان مقاله :
Shadow Detection Based on Combinations of HSV Color Space and Orthogonal Transformation in Surveillance Videos
پديدآورندگان :
Moghimi Mohammad Kazem نويسنده , Pourghassem Hossein نويسنده Young Research Club-Islamic Azad University- Najafabad Branch, Iran
كليدواژه :
Shadow detection , HSV color space , Moving Average , Orthogonal transformation , background extraction
عنوان كنفرانس :
مجموعه مقالات دوازدهمين كنفرانس سيستم هاي هوشمند ايران
چكيده فارسي :
shadow removing is an important issue in
performance of intelligent transportation system. In this paper,
a synthetic shadow detection algorithm using combination of
orthogonal transformation and HSV color space is proposed.
In this algorithm, orthogonal transformation and HSV color
space are applied to improve the performance of shadow
detection. At first, the current and background images are
transferred from RGB color space to HSV color space, then
using combination of orthogonal transformation and shadow
color feature in HSV color space, the shadow is detected in the
image blocks. Our proposed algorithm is evaluated on a real
and operation videos. The obtained results by our algorithm
demonstrate the efficiently and effectiveness of this algorithm
in intelligent transportation system application.
شماره مدرك كنفرانس :
3817034