attack

视网膜血管检测的Gabor变换和机器学习，教程 本教程将演示如何Gabor变换和广义 的线性模型（GLM）可用于视网膜血管检测 图像。 ，我们将尝试检测视网膜血管从 的训练图像，首先，Gabor滤波器与图像卷积。 GLM将使用Gabor变换的图像特征确定 （独立变量）和容器的位置 为结果（因变量）。( Retinal Vessel Detection by Gabor Transform and Machine Learning, a Tutorial This tutorial will demonstrate how Gabor transforms and generalized linear model (GLM) can be used for detection of retinal vessels in images. Specifically, we will attempt to detect the retinal vessels a training image , by first, convoluting multiple Gabor filters with the image. A GLM will be determined using the Gabor transformed images as features (the independent variables), and the locations of the vessels as the outcome (the dependent variable).)

LMS算法函数，基于自适应滤波器的噪声抵消算法研究(LMS algorithm function, based on adaptive filter noise cancellation algorithm)

识别分割图像中不同颜色的部分，并分别显示出来(Identifying portion dividing the image in different colors, and were displayed)

用帧差法找出运动物体，并用形态学滤波恢复物体(Identify moving objects in frame difference method and morphological filtering restore objects)

一种基于改进DRLSE的运动目标分割方法,为了得到精准、连续的运动目标轮廓，提出将帧间差分法和改进的距离规则水平集演化(DRLSE)方法结合应用于运动目标分割。(In order to get an accurate and continuous contour of moving target, a novel method to segment moving object by combining the frame difference and an improved distance regularized level set evolution (DRLSE) is proposed. )

结构张量来进行自适应正则化图像重建，单幅图像重建(Structure tensor adaptive regularized image reconstruction, a single image reconstruction)

自己编写的广义霍夫变换，里面有测试图片，可以作为学习霍夫变换的入门(I have written a generalized Hough transform, there are test images, the Hough transform can be started as a learning)

利用相位相关法实现了图像的匹配，这种方法的优点是提取速度快，方法简单，运算量少。(Using the phase correlation method to realize the image matching, the advantage of this method is the extraction method is simple, fast, less computation.)

该数字图像处理文件有很强的修改能力，可以仔细的分析每一个频域不同条件下的实验结果分析。有很强的处理图像能力(The digital image processing of documents has a strong ability to change and be more careful analysis of each under different conditions, a frequency-domain analysis of the experimental results. Has a strong ability to deal with images)

人脸图像配准，将同一场景的两幅或多幅图像进行对准，可以实现人脸归一化(Face image registration, the same scene two or more images for the alignment can be achieved face normalization)