• Background subtraction and frame difference method are commonly used moving objects detection methods.

    背景差法和帧间差法都是常用的运动目标检测方法。

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  • The result shows this algorithm is better than frame difference method, background difference method and road mark method.

    结果显示该算法明显优于帧差法、背景差法、路面标记法。

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  • It combines organically the edge detection method and the improved frame difference method to effectively detect the moving and stagnant vehicles simultaneously.

    将边缘检测法与改进帧差法进行有机结合,有效地实现了运动和静止车辆的同时检测。

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  • The mathematical morphological filtering technique based upon frame difference method has been push forward and the basic program flow chart for this algorithm is also set forth.

    在此基础上选择数学形态学滤波方法,设计了基于帧间差分法的数学形态学图像滤波处理算法,并设计了算法的程序流程。

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  • The moving target detection method based on the three frame difference and background difference method was proposed, which is simply and fast to realize.

    提出了利用三帧差分法和背景差分法对运动目标进行检测的方法,该运动检测的方法实现比较简单、速度快。

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  • We used frame difference and region growing method to divide target and get main color information.

    对于待跟踪的运动目标,采用三帧差和区域增长法分割目标并得到主颜色信息。

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  • According to the imaging difference of target, background clutter and noise, a moving small target detection method based on spacial high-pass filtering and N-frame track accumulating is presented.

    根据目标、背景干扰和噪声在红外序列图像中的差异,提出了一种基于空间高通滤波和时间域上N帧轨迹积累的运动小目标检测方法。

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  • In image processing, mathematical morphology, frame difference, ultra limits domain method of average and labeling of connected domain is introduced essentially.

    图像处理中采用了数学形态学、差值法、超限领域平均法以及连通域识别与标记算法来实现客流信息的提取。

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  • Motion object region is extracted from multi-frame images in image sequences by using similar difference method.

    它采用类似差分的方法从图像序列的多帧图像中检测出运动目标区域。

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  • The moving target detection method based on the three frame difference and background difference method was proposed, which is simply and fast to realize.

    在对帧间差分算法进行分析的基础上,建立了基于帧间差分算法的目标探测识别系统,提出了针对该算法的脉冲光干扰方法。

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  • The pixel-matching two-difference algorithm and two histogram comparison are used for shot detection, a method of extraction shot key frame based on distance of adjacent frame is presented.

    首先使用改进了的像素匹配二次差分法结合双阈值法进行镜头突变和渐变的检测,然后对镜头内的帧间距离进行判断来提取关键帧;

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  • This paper proposes and implements a moving object segmentation method, which based on inter-frame difference.

    为此,文章提出并实现了一种基于互帧差的视频运动对象分割方法。

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  • This method bears not only the characteristic "exact to survey object" of background subtraction but also the characteristic "robust to lighting variations" of frame difference.

    该方法把背景差法的“准确监测物体”与帧间差法的“对光线具有较强的适应性”结合起来。

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  • In the process of object detection, the inter-frame difference object detection method and symmetrical inter-frame difference object detection method based on gray were used respectively.

    在目标检测过程中,分别利用单目视觉下基于灰度的连续帧间差分法和对称差分法实现了目标检测。

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  • According to the study of main motion detection and moving objects extraction methods, a new method combining frame-difference and background-difference was put forward.

    在对视频监控中运动目标检测识别常用算法进行研究的基础上,本文提出了一种新的基于两帧差分法和背景差分法相结合的运动目标检测方法。

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  • The paper introduces several methods for vision-surveillance using background subtraction, frame-difference method, symmetrical differencing and a method based on RGB image.

    介绍了在视觉监控领域经常用到的几种运动人体检测算法,如背景减除法、帧差法、对称差分法、基于RGB图像的运动检测法。

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  • Firstly, a rough motion mask is obtained by introducing a motion area segmentation method based on an improved accumulative frame- difference algorithm and optimal threshold segmentation.

    利用小波包分析算法提取出单帧图像的边缘信息并获得细化的目标区域边缘图;

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  • According to continuity of gray-value of targets in inter-frame, the frame-difference method is proposed to detect the moving objects in this paper.

    考虑到视频序列图像具有帧间连续性,本文通过帧间差分的方法检测运动车辆。

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  • According to continuity of gray-value of targets in inter-frame, the frame-difference method is proposed to detect the moving objects in this paper.

    考虑到视频序列图像具有帧间连续性,本文通过帧间差分的方法检测运动车辆。

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