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meanshift

于 2020-06-25 发布 文件大小:11714KB
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  基于meanshift算法最全面的资料收集，是本人长期收集该算法的结晶，里面有均值漂移算法的word文档，PPT资料，基于meanshift的目标跟踪算法（MATLAB），还有相应的文章，下了绝不后悔，将心比心，互惠互利。(Meanshift algorithm based on the most comprehensive data collection, is a long time, I collected the crystallization of the algorithm, which has mean-shift algorithm word document, PPT data, meanshift target tracking algorithm based on (MATLAB), there is a corresponding article, in no way under the regret, Care, and mutual benefits.)

文件列表：

meanshift文章、PPT、word文档、基于meanshift的跟踪程序
.....................................................\An Introduction to Mean Shift.doc
.....................................................\meanshift.pdf
.....................................................\meanshift均值平移跟踪算法中核函数窗宽的自动选取代码，根据目标大小变化核窗宽，使得当目标出现大小变化时准确跟踪到目标中心
.....................................................\.......................................................................................................................\color_example.m
.....................................................\.......................................................................................................................\color_object_tracking2.m
.....................................................\.......................................................................................................................\compute_kernelmatrix.m
.....................................................\.......................................................................................................................\compute_k_hist.m
.....................................................\.......................................................................................................................\compute_wi.m
.....................................................\.......................................................................................................................\object_tracking.m
.....................................................\.......................................................................................................................\readme.m
.....................................................\.......................................................................................................................\show_target.m
.....................................................\.......................................................................................................................\track.m
.....................................................\.......................................................................................................................\说明.txt
.....................................................\mean_shift.ppt
.....................................................\一个外国人写的很好的meanshift聚类算法，有例程，可运行
.....................................................\.....................................................\Mean Shift A Robust Approach Toward Feature Space Analysis.pdf
.....................................................\.....................................................\MeanShiftCluster.m
.....................................................\.....................................................\testMeanShift.m
.....................................................\实现了基于mean-shift的图像检索，实现了比较两图像的相似度，选择最相近的图片
.....................................................\..........................................................................\meanshift


.....................................................\..........................................................................\.........\comparing.m
.....................................................\..........................................................................\.........\getkernalmatrix.m
.....................................................\..........................................................................\.........\getmeanshiftsegment.m
.....................................................\..........................................................................\.........\getsimilarity.m
.....................................................\..........................................................................\.........\get_cluster_property.m
.....................................................\..........................................................................\.........\hs_err_pid4076.log
.....................................................\..........................................................................\.........\meanshiftsmooth.m
.....................................................\..........................................................................\.........\myedge.m

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  • 2
    说明：  边缘特征的提取就是求图像梯度的局部最大值和方向。实际计算中，以微分算子的形式表示，并采用快速卷积函数来实现。常用的算子有微分算子，拉普拉斯算子，Canny算子等。其中Canny边缘检测是一种较新的边缘检测算子，具有较好的边缘检测性能，得到越来越广泛的应用。Canny边缘检测法利用高斯函数的一阶微分，它能在噪声抑制和边缘检测之间取得较好的平衡(Edge feature extraction is to seek the local maximum of image gradient and orientation. The actual calculation to the form of differential operator representation, and using fast convolution function to achieve. Commonly used operators are differential operators, Laplace operator, Canny operator and so on. Canny edge detection which is a relatively new edge detection operator, and has good edge detection performance, get more and more widely used. Canny edge detection method using first derivative of Gaussian function, it can in the noise suppression and edge detection to achieve a better balance between)
    2010-06-16 08:36:49下载
    积分：1
  • 图像处理
    说明：  图像处理实验matlab的图像预处理：边缘检测、二值化、形态学滤波、灰度化(Image processing experiment matlab image preprocessing:Edge detection, binarization, morphological filtering)
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    2013-09-14 11:35:48下载
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  • 基于无损压缩的加密图像可逆信息隐藏_郑淑丽
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    2013-07-23 21:44:55下载
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  • IRandvisbletuxiangpeizhun
    针对可见光与红外图像的特点和难点，提出了可见光与红外图像配准与融合中的关键技术，即: 使用新型的基于一维最大类间方差和最大连通性测量的图像分割方法对源图像进行分割来更好地实行图像粗 配准 使用新型的特征点提取方法，特征点的匹配及误匹配的消除来更好地实行图像精配准 采用新型的基 于区域的树状小波活性测度计算来实现树状小波图像融合 利用自生成神经网络来实现模栩图像融合. (For visible light and infrared images of the characteristics and difficulties, a visual and infrared image registration and integration of key technologies, namely: the use of new one-dimensional based on the largest variance between-class connectivity and the largest measuring method of image segmentation source image segmentation to better implementation of coarse image registration the use of a new type of feature point extraction method, feature points of the match and the elimination of false matches to better the implementation of image fine registration the use of new tree-based wavelet calculated to measure the achievement of the activity tree wavelet image fusion the use of self-generating neural network to achieve image fusion Xu mode.)
    2009-04-20 11:49:14下载
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  • 123
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