但是这种基于图像灰度均值分割的形心跟踪算法对于小目标图像都会跟踪失败。
However, the centroid tracking algorithm based on the image gray-mean segmentation fails when tracking small target images.
该系统运用差分图像法，通过阈值图像分割来检测运动目标，并采用形心跟踪算法来自动跟踪目标。
This system detected motion target using difference image method through threshold image segmentation, then automatically tracked target by using centroid tracking algorithm.
首先把图像序列中相对静止的部分提取出来作为背景，利用差分图像对道路上的运动物体进行分割，并在此基础上实现对每条车道上的车辆的跟踪。
Firstly the relatively static proportion of the video was extracted and the moving objects were segmented using differencing image algorithm. Then vehicles were tracked in divided road lanes.
为了使图像跟踪系统能根据图像特征自适应选取分割算法，给出了一种基于粗糙集理论的图像分割智能决策方法。
In order that the image tracking system can select segmentation algorithm itself according to the object image feature, this paper presents an intelligent decision method of image segmentation.
均值平移是一种有效的统计迭代算法，已广泛应用于聚类分析、跟踪、图像分割、图像平滑、滤波、图像边缘提取和信息融合等方面。
Mean shift is an effective iterative algorithm widely used in clustering, tracking, segmentation, discontinuity preserving smoothing, filtering, edge detection, and information fusion etc.
最大类间方差法是一种常用而有效的图像分割算法，但由于计算量较大，不适宜于红外成像跟踪系统中高帧频的实时图像处理。
The Otsu's method is an effective algorithm for image segmentation. But it is unfit for the real-time image processing in the high frame rate infrared imaging tracking system for it is time-consuming.
图像分割和目标跟踪技术是计算机视觉领域的重要的研究方向，在模式识别、图像编辑、智能监控等领域有着广泛的应用。
Image segmentation and object tracking are important research task in the field of computer vision, they are wildly used in areas such as pattern recognition, image editing, intelligent surveillance.
该方法利用相邻两帧图像数据的相关性，根据跟踪区域的灰度信息自动调节每帧图像的分割阈值，使在跟踪区域内的目标得到了较好的分割效果。
In order to get real time tracing, only the gray information of the trace region is considered. At last the algorithm is used in a serial image...
该方法利用相邻两帧图像数据的相关性，根据跟踪区域的灰度信息自动调节每帧图像的分割阈值，使在跟踪区域内的目标得到了较好的分割效果。
In order to get real time tracing, only the gray information of the trace region is considered. At last the algorithm is used in a serial image...
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