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pzernike

于 2008-10-16 发布 文件大小:1KB
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说明:  伪Zernike矩特征提取,Zernike矩特征提取,供参考,很有用(Pseudo-Zernike moment feature extraction, Zernike moment feature extraction, for reference, very useful)

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  • cry
    说明:  通过IDL,简单实现灰度变换,彩色变换等基本操作,包括图片打开保存拖拽显示(Simple implementation of gray level transformation, color transformation and other basic operations)
    2019-04-23 11:13:51下载
    积分:1
  • feijiejeijiance
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    2021-05-13 03:30:03下载
    积分:1
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    数字图像处理实验-图像处理-含实验题目及源代码(Pseudo-Color Image Processing (a) Implement Fig. 6.23, with the characteristic that you can specify two ranges of gray-level values for the input image and your program will output an RGB image whose pixels have a specified color corresponding to one range of gray levels in the input image, and the remaining pixels in the RGB image have the same shade of gray as they had in the input image. You can limit the input colors to all the colors in Fig. 6.4(a). (b) Download the image in Fig. 1.10(4) and process it with your program so that the river appears yellow and the rest of the pixels are the same shades of gray as in the input image. It is acceptable to have isolated specs in the image that also appear yellow, but these should be kept as few as possible by proper choice of the two gray-level bands that you input into your program.)
    2017-11-06 16:52:41下载
    积分:1
  • four
    说明:  对指定的一幅含有多个目标的灰度图像,进行基于阈值的图像分割处理,对结果图像进行基于数学形态学的后处理设计,以得到更理想的目标区域。最后对结果图像进行区域标记(以颜色区分不同区域)并提取目标个数、各目标区域的面积、圆形度等特征。(The gray image with multiple targets is segmented based on threshold, and the result image is designed based on mathematical morphology to get a better target area. Finally, we mark the region of the result image (distinguish different regions by color) and extract the number of targets, the area of each target region, roundness and other features.)
    2020-04-26 23:04:28下载
    积分:1
  • shape_context
    包含canny edge detector 和 shape context 的优化计算。(Contains the canny edge detector and the shape context of the optimization calculation.)
    2008-04-20 23:22:04下载
    积分:1
  • WindowsFormsImage2
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    2011-11-19 09:54:39下载
    积分:1
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    目前MATLAB里边对于多点计算仿射矩阵普遍采用RANSAC法,但是比较麻烦计算量也相对较大,通过最小二乘法来进行仿射矩阵的估计能够大大提高该效率,所以奉上自己在实验室写的仿射矩阵估计函数,来弥补matlab函数库在这方面的不足。(The MATLAB inside for calculating affine matrix commonly used RANSAC method, but more trouble calculation is relatively large, estimated by the least squares method to the affine matrix can greatly improve the efficiency, so give yourself in laboratory to write the estimated affine matrix function, to compensate for the lack of MATLAB Library in this area.)
    2018-02-01 17:11:33下载
    积分:1
  • GMM高斯混合模型进行背景建模(Matlab)
    转:https://blog.csdn.net/jinshengtao/article/details/26278725 混合高斯背景建模是基于像素样本统计信息的背景表示方法,利用像素在较长时间内大量样本值的概率密度等统计信息(如模式数量、每个模式的均值和标准差)表示背景,然后使用统计差分(如3σ原则)进行目标像素判断,可以对复杂动态背景进行建模,计算量较大。 在混合高斯背景模型中,认为像素之间的颜色信息互不相关,对各像素点的处理都是相互独立的。对于视频图像中的每一个像素点,其值在序列图像中的变化可看作是不断产生像素值的随机过程,即用高斯分布来描述每个像素点的颜色呈现规律单模态(单峰),多模态(多峰)(Gaussian mixture background modeling is a background representation method based on the statistical information of pixel samples. Statistical information such as the number of patterns, the mean and standard deviation of each pattern are used to represent the background. Statistical difference (such as 3_principle) is used to judge the target pixel. Complex dynamic background modeling has a large amount of computation. In the Gaussian mixture background model, it is considered that the color information between pixels is uncorrelated and the processing of each pixel is independent of each other. For each pixel in a video image, the change of its value in a sequential image can be seen as a random process that produces pixel values continuously, i.e. Gaussian distribution is used to describe the regularity of color rendering of each pixel in single mode (single peak) and multi-mode (multi-peak).)
    2020-11-01 09:49:54下载
    积分:1
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    2012-03-09 22:01:01下载
    积分:1
  • MATLAB
    实验2绿叶变色,实验3图像数字化显示,实验4图像类型转换,实验5对比度增强,实验6直方图均衡化和规定化,实验7噪声添加和空域滤波,实验8边缘增强和边缘检测,实验9彩色图像增强,fft,dct,dwt变化及压缩,滤波器,实验20运动退化和维纳波复原,实验21图像的几何畸形校正等实验的代码和报告(Experiment 2 leaves change color, 3 digital image display, the image type conversion, 4 5 contrast enhancement experiment, the experiment 6, histogram equalization and regulations 7 noise adding and spatial filtering experiment, experiment and edge enhancement and edge detection, the experiments of 9 color image enhancement, FFT and DCT, DWT and compression, filter, degradation experiment of 20 movement and wiener recovery, experiment 21 image geometric deformity correction code and report)
    2016-05-11 21:12:47下载
    积分:1
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