[0024] 所述背景减除法（Background subtraction method）是目前目标检测中最常用的 方法之一，它将图像分为背景和前景，对背景进行建模，然后用当前帧与背景图像的差分来
基于12个网页-相关网页
In order to overcome the deficiency of updating the background model and removing the shadow when the background subtraction method is applied to detect moving objects,an improved algorithm based on the single-Gaussian background model is proposed.
针对背景减除法应用于运动目标检测中的背景模型更新和阴影消除问题,提出了一种改进的单高斯背景模型估计算法和快速的阴影消除方法。
参考来源 - 基于单高斯背景模型运动目标检测方法的改进For the motion blur resulting from relative motion, projection restoration method was used to restore the image. The background subtraction method was used to extracted foreground objects.
引入信噪比(SNR)作为判断参数,判定样本图像是否需要去噪,以减少运算量;对图像中因相对运动而产生的运动模糊,使用投影恢复法予以消除;采用背景差法提取前景目标,提出背景自适应算法更新现场背景,抑制现场光照变化对目标检测的影响。
参考来源 - 基于ARM的人员智能引导系统的设计·2,447,543篇论文数据，部分数据来源于NoteExpress
In view of the faults of traditional method, a new background subtraction method for video image sequence is proposed.
针对传统背景提取算法的不足，提出一种新的视频序列背景提取方法。
This paper proposes an improved background subtraction method based on Gaussian mixture background model which can not deal with the problem of scene light rapid change.
文中针对混合高斯模型不能应对光线突变的问题，提出了一种改进的背景模型。
This new algorithm USES the background subtraction method to get the foreground image, and then gets the binary image using threshold value and makes the morphology processing.
该算法利用背景差法获得前景图像，然后进行二值化和形态学处理，再和背景帧进行比较来对滞留和搬移物体进行检测和分类。
应用推荐