KernelFisher

说明：  在matlab下实现信号频谱分析：利用快速付里叶变换FFT得到下列信号的频谱，并绘制信号及频图形：1.长2s的方波信号，频率f=10Hz (In matlab signal spectrum analysis: the fast in leaf transform FFT get pay of spectrum, the signal and drew the signal and frequency graphics: 1. The long 2s, frequency f = square wave signal 10Hz )

说明：  使用sift进行的图像拼接，matlab语言实现(Image mosaic using sift)

指纹识别系统，包括指纹图像预处理，特征点提取，采用点模式匹配。(Fingerprint identification systems, including fingerprint image preprocessing, feature extraction, using point pattern matching.)

fcm聚类分析,用距离方法进行聚类画图，有一定的可操作性(FCM clustering analysis, using distance method for clustering drawing, has a certain operability.)

自己编的利用FreeImage库分割图像的程序,可以将一个图片分成5个不同区域的图片,主要用于壁纸分割.(Own use FreeImage library image segmentation procedure, a picture can be divided into five different regions of the picture, the main partition for wallpaper.)

本程序为matlab写的morphing. 将不同角度拍摄之影像做morphing, 成为一摄影机连续移动拍摄同一物品的影带，可作为VR之用. (the procedures written in Matlab for morphing. Different angle Imaging filming done morp hing, as a continuous mobile cameras filming the same article video tapes can be used as a VR.)

说明：  在VC++下基于MRF来进行的图像分割源代码(In VC++ For MRF-based image segmentation source code)

视频水印matlab源码，此为第三个压缩包，在水印领域的爱好者可以下载作为参考(Video Watermarking Matlab source, which is the third-compressed, Watermark in the field of lovers can download as a reference)

首先生成如下形式的图片：图中的白条为7象素宽，210象素高，白条间的宽度为17象素。 应用多种滤波器进行处理：算术均值，几何均值，谐波均值，逆谐波均值，中值滤波，中点滤波，最大值、最小值滤波等。注意，需改变模板大小。详细比较上述的结果，并分析原因。 (First generation following form images: figure IOUs 7 pixels wide, 210 pixels high, the width is 17 pixels between IOUs. Using a variety of filters for processing: the arithmetic mean, geometric mean, harmonic mean, inverse harmonic mean, median filtering, filtering midpoint, maximum, minimum filtering. Note that the need to change the template size. A detailed comparison of these results and analyze the reasons.)

EDLines是一种快速直线检测算子，2012年在ICCV上提出，也是目前处理直线检测最快的算法之一，该算法包含三个步骤：（1）边缘提取：利用Edge Drawing (ED)算法[28,29]从灰度图像中提取边缘片段；（2）线段检测：利用最小二乘法提取直线段；（3）线段确认：遵循Helmholtz定律，从已提取的直线段中摒弃虚假线段。EDLines算法的优越性得益于Edge Drawing (ED)算法能够从灰度图像中准确、快速、稳定地提取出光滑、完整的边缘片段。Edge Drawing (ED)算法包含以下步骤： （1）采用size=5*5,σ=1的高斯核对灰度图像进行平滑滤波，去除噪声； （2）采用一种常用的梯度算子，如Prewitt、Sobel或Scharr等计算平滑后图像中每个像素点的梯度幅度和梯度方向； （3）将梯度图中邻域内幅度最大的像素点标记为锚点，这些锚点成为图像边缘点(edge elements)的概率很大； （4）将相邻的锚点连接成边缘线。从一个锚点起始，ED利用相邻像素的梯度幅度和方向在梯度为最大值的锚点之间游走。 (Edge Drawing (ED) is our recently-proposed, novel, fast edge detection algorithm. What makes ED stand out the existing edge detectors, e.g., Canny, is the following: While the other edge detectors give out a binary edge image as output, where the etected edge pixels are usually independent, discontinuous entities ED produces a set of edge segments, which are clean, contiguous, i.e., connected, chains of edge pixels. Thus, while the output of the other edge detectors requires urther processing to generate potential object boundaries, which may not even be possible or result in inaccuracies ED not only produces perfectly connected object boundaries by default, but it also achieves this in blazing speed compared to other edge detector.)