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۱Bayesian Illumination Invariant Motion Detection Using a New Adaptive Threshold
نویسنده(ها): ،
اطلاعات انتشار: چهاردهمین کنفرانس دانشجویی مهندسی برق ایران، سال
تعداد صفحات: ۴
Detection of moving objects plays a very important role in video processing of many vision applications. The vision systems constituting of image processing algorithms are widely implemented and exploited in various applications such as traffic control, video surveillance of objects, and etc. Most basic change detection algorithms assume that the illumination of relative scene will remain constant. However, this assumption is not necessarily valid particularly outside a well–controlled laboratory setup. In this paper, a novel illumination–invariant method of change detection has been presented which is insensitive to varying illumination. The proposed algorithm has been based on a Bayesian change detection method using a threshold that is adaptively controlled so that the effects of the illumination of image frames are minimized. Proposed adaptation algorithm employs distance measure.<\div>

۲A New Illumination–Invariant Method of MovingObject Detection for Video Surveillance Systems
نویسنده(ها): ،
اطلاعات انتشار: هفتمین کنفرانس ماشین بینایی و پردازش تصویر، سال
تعداد صفحات: ۵
Visual surveillance especially for humans and vehiclesis currently one of the most active research topics in computervision. In this paper, a new method is introduced for thedetection of moving objects in surveillance applications. Theproposed method relies on a model assigning a vector of graylevels to every pixel location of the current image. The vectorrepresents information on the neighborhood region of that pixel.Using norm of the vectors in two consecutive frames and theBayesian change detection algorithm, we introduce a novelmethod for moving object detection which is robust to noise andillumination changes. Also, it is insensitive to repeated motions inthe background.<\div>
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