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基于不精确拉格郞日算子法的低秩矩阵重构程序,可以用于图像分割,将目标图像分割为背景和前景,从而将前景分离出来。-Lagrangian method based on imprecise low rank matrix reconstruction procedures can be used for image segmentation, the target image into background and foreground, which will separate the foregr
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基于特征值分解的低秩图像分解程序,将目标图像分割为背景和前景之和,参数可以在运行中依据目标图像的实际情况进行调节,注意目标图像不要过大,否则会溢出。-Based on Eigenvalue Decomposition of low rank image decomposition process, the target image into the background and the foreground and, in the operation parameters can be base
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介绍了一种显著性检测,程序可以直接运行,可以得到显著图像,有图像源。-propose a bottom-up visual saliency detection algorithm. Different most previous methods that mainly concentrate on image object, we take both background and foreground into consideration.
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直方图拉伸是通过对比度拉伸对直方图进行调整,从而“扩大”前景和背景灰度的差别,以达到增强对比度的目的-Histogram stretching histogram is adjusted by contrast stretching, thereby " expand" the difference between the foreground and background of gray, in order to achieve the purpose of enhancin
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实现图像分割功能的matlab程序,有效分离指纹前景和背景,方便下面的操作-Image segmentation function of the matlab program, effective separation of the foreground and background, to facilitate the following operations
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图像分割是图像处理的重要步骤, 由于彩色图像含有的信息比灰度图像还多, 因而对彩色图像分割的研
究越来越受到人们的关注. 提出一种新的基于RGB 空间颜色相似性的彩色图像分割方法. 首先比较各种颜色模
型的优势与不足, 然后根据RGB 颜色空间的颜色信息和亮度信息提出一种计算在RGB 空间下颜色相似性的方
法, 再结合提出的图像颜色分量计算方法, 从而形成颜色分类地图, 最后根据颜色分类图进行像素划分, 得到分
割结果. 实验在Matlab 平台上进行, 结果表明: 对于颜色分明
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ViBe是一种像素级的背景建模、前景检测算法,该算法主要不同之处是背景模型的更新策略,随机选择需要替换的像素的样本,随机选择邻域像素进行更新。-ViBe is pixel-level background for modeling, foreground detection algorithm, which is the main difference between the background model update strategy, randomly selected sample o
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用libsvm来实现图像分割,测试图片用的亦是25cases和40cases中的那个littleduck测试图片。主体程序思想为25cases中的代码过程,改进之处为可以让用户利用ginput来提取背景的样本点和前景(待分割出来的目标)的样本点作为训练样本,而不需实现指定背景和前景的样本点,也不用额外的小软件来查看某点的RGB值,ginput即可。-With libsvm to image segmentation, test picture is also used in 25cases an
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一个新闻后台及前台控制 一个新闻后台及前台控制-A news background and foreground control
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文件实现了目标检测,可以很清楚的区分前景和背景。(The file implements the target detection, which can distinguish the foreground and the background clearly.)
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能够初步实现静态背景下的前景提取,能够为初学者提供一定的借鉴。(It can realize foreground extraction in static background,
It can provide some reference for beginners.)
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混合高斯模型,用于背景变化无抖动的目标的前景提取(The hybrid Gauss model is used for foreground extraction of background invariant targets without jitter)
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用于车辆检测背景建模 通过混合高斯将前景与北京分离(Vehicle tracking background modeling is used to extract foreground)
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帧间差MATLAB提取静态背景的前景信息(Frame difference MATLAB extracts foreground information from static background)
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用高斯模型算法来处理视频,提取前景信息,适合动态背景(Gauss model algorithm is used to process video and extract foreground information, which is suitable for dynamic background)
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用vibe算法提取动态背景的前景信息,背景为白色(Vibe algorithm is used to extract foreground information of the dynamic background, the background is white)
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光流法处理视频的前景信息的提取,该算法适应于静态背景(Optical flow processing of video foreground information extraction, the algorithm is adapted to the static background)
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运动估计算法去提取动态背景的前景信息,效果不是很好(Motion estimation algorithm to extract the foreground information of the dynamic background, the effect is not very good)
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ViBe算法是由Olivier Barnich 和 Marc Van Droogenbroeck在2011年提出的一种背景建模方法。该算法采用邻域像素来创建背景模型,通过比对背景模型和当前输入像素值来检测前景.(ViBe algorithm is a background modeling method proposed by Olivier Barnich and Marc Van Droogenbroeck in 2011. The neighborhood pixels are used
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采用多个高斯分布的方式来描述背景像素点的特征,在线地更新参数和权重,实现运动检测和前景提取的同步进行,即采用混合高斯背景算法进行建模,以降低动态背景的干扰。(The characteristics of the background pixel are described by several Gaussian distributions, and the parameters and weights are updated online. Synchronization of motion d
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