WPF学习- 不规则窗体 实例源码下载

用于人脸识别边缘检测，实现5个尺度、8个方向的检测。(Edge detection for face recognition)

说明：  利用Em算法进行图像分割的代码，可以运行，代码简短清晰，有利于初学者，希望对你有用(Em algorithm using image segmentation code, you can run, code clear brief will help beginners, in the hope that useful to you)

指纹图像的增强，效果很好,计算指纹的频率和方向，采用Gabor的方式增强(Fingerprint image enhancement, the effect is very good, calculate the frequency and direction of fingerprints, using Gabor way to enhance)

说明：  关于全变分的图像修复算法。。 。。 。。 。。 (On the whole variational image restoration algorithm. . . . . . . .)

传统滤波方式如均值滤波，中值滤波，维纳滤波对图像去噪的处理以及自适应中值滤波对图像去噪。(Traditional filtering methods such as mean filtering, median filtering, wiener filtering for image denoising processing and adaptive median filter for image denoising.)

Opencv处理图像，用ostu法实现图像的二值化(Opencv image processing, using ostu method to achieve image binarization)

说明：  1.学习使用fft2,ifft2,fftshift,ifftshift函数。用fft2函数对”lena.bmp”做二维傅立叶变换，并显示其频谱，用fftshift函数将频谱坐标原点移动到图像中心。用ifft2函数做傅立叶反变换。（提示：显示频谱时，可以先对频谱取对数，这样可以压缩动态范围很大的频谱，获得更好的显示效果）(1. Learn to use fft2, ifft2, fftshift, ifftshift functions. With the FFT 2 function, the lena.bmp'The two-dimensional Fourier transform is performed and the spectrum is displayed. The origin of the spectrum coordinate is moved to the center of the image by using the FFT shift function. The inverse Fourier transform is done with ifft2 function. (Note: when displaying the spectrum, the logarithm of the spectrum can be taken first, so that the spectrum with a large dynamic range can be compressed to obtain better display effect.))

FIR滤波器的C语言实现 C语言源程序代码及解析(FIR filter, the C language realization C source code and analytical)

基于sift的图片近似拷贝检测技术算法的实现(Sift-based image copy detection technology approximation algorithm)

　　本函数选用阈值分割的方法来完成瞳孔定位。根据图像的灰度分布特性，瞳孔部分的灰度值最小，其次为虹膜部分，最大的为巩膜部分。因此在灰度直方图中，第一个大峰值的邻域即是瞳孔所在区域。(Function selects the threshold segmentation method to accomplish the pupil location. Based on image gray distribution features, the pupil part of the grey value of the minimum, followed by the iris part, the biggest part of sclera. So in gray level histogram, the peak value of the first big neighborhood is the pupil area.)