gabor

说明：  Demo for smoke effects on old NVIDIA GPUs.

说明：  LSB替换隐写软件，该软件能把ASCII码嵌入到图像中，其载体图像是24位的BMP格式图像(LSB replaces steganography software, which can embed ASCII code into image, and its carrier image is 24 bit BMP format image)

图像的特征用到了Dense Sift，通过Bag of Words词袋模型进行描述，当然一般来说是用训练集的来构建词典，因为我们还没有测试集呢。虽然测试集是你拿来测试的，但是实际应用中谁知道测试的图片是啥，所以构建BoW词典我这里也只用训练集。 其实BoW的思想很简单，虽然很多人也问过我，但是只要理解了如何构建词典以及如何将图像映射到词典维上去就行了，面试中也经常问到我这个问题，不知道你们都怎么用生动形象的语言来描述这个问题？ 用BoW描述完图像之后，指的是将训练集以及测试集的图像都用BoW模型描述了，就可以用SVM训练分类模型进行分类了。 在这里除了用SVM的RBF核，还自己定义了一种核： histogram intersection kernel，直方图正交核。因为很多论文说这个核好，并且实验结果很显然。能从理论上证明一下么？通过自定义核也可以了解怎么使用自定义核来用SVM进行分类。(Image features used in a Dense Sift, by the Bag of Words bag model to describe the word, of course, the training set is generally used to build the dictionary, because we do not test set. Although the test set is used as the test you, but who knows the practical application of the test image is valid, so I am here to build BoW dictionary only the training set. In fact, BoW idea is very simple, although many people have asked me, but as long as you understand how to build a dictionary and how to image map to the dictionary D up on the line, and interviews are often asked me this question, do not know you all how to use vivid language to describe this problem? After complete description of the image with BoW, refers to the training set and test set of images are described with the BoW model, the training of SVM classification model can be classified. Apart from having to use the RBF kernel SVM, but also their own definition of a nuclear: histogram intersection kernel, histogram )

运动目标的给总与识别，可以实时显示目标的运动轨迹，支持高速相机实时处理视频数据，并可以获得运动目标的轮廓矩等信息(Moving target to the total and the identification of moving targets in real-time display track, real-time processing to support high-speed video camera and moving target access to information such as contour moments)

这些代码是有关数字图像处理的一些算法，大家有需要的，可以在里面找些与自己相关的(These codes are some of the digital image processing algorithms, we need, in which you can find some with their associated)

使用adaboost方法进行人脸检测,图象库自己添加。(Face detection with adaboost method.)

说明：  噪声估计法，先定位噪声点，再实行去噪处理(Noise estimation method, first locate the noise points, then implement denoising.)

一个基于MATLAB环境的图像分割算法，运用最大熵解决图像分割问题。(An image segmentation algorithm based on MATLAB environment is applied to solve the problem of image segmentation using maximum entropy.)

在图像去卷积算法引入先验模型的应用,主要是建立马尔可夫随机场先验模型.很大程度上改进了去卷积的效果,更多的保持了图像的边缘特征.(In image deconvolution algorithm Application of the introduction of a priori model, mainly the establishment of Markov random field a priori model. A large extent, improved the effectiveness of deconvolution, more to maintain the image of the edge feature.)

人耳识别，包含图像预处理，图像特征点的提取，比较实用(Ear recognition)