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
تعداد صفحه :
6
كليدواژه :
Shadow detection , HSV color space , Moving Average , Orthogonal transformation , background extraction
عنوان كنفرانس :
مجموعه مقالات دوازدهمين كنفرانس سيستم هاي هوشمند ايران
زبان مدرك :
فارسی
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
سال انتشار :
2014
از صفحه :
1
تا صفحه :
6
سال انتشار :
0
لينک به اين مدرک :
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