matlab-code

二维otsu的快速实验算法，具体可参考相应的文献。(Two-dimensional Otsu rapid test algorithm, specific reference to the corresponding literature.)

基于LSB的音频水印嵌入提取算法，隐藏信息为一个文本文件(Extraction algorithm, the LSB-based audio watermark embedding hidden information into a text file)

该算法先通过七点进行M估计，然后挑选三点进行精确匹配运算(This algorithm firstly the fuzzy matching to achieve slightly at the beginning of localization, to achieve accurate positioning on the basis of improve the accuracy simulation)

利用遗传算法进行图像分割的源程序.基于matlab平台,适合于一维和二维分割.(using genetic algorithms for image segmentation of the source. Matlab-based platform, in a fit- and two-dimensional segmentation.)

Kaiming He的导向滤波算法的源代码(Guided filter source code Kaiming He)

说明：  harris角点检测算法，用于图像拼接的配准(harris corner detection algorithm for image mosaic of the registration)

说明：  对一副已经给出的图像进行中值滤波处理，利用罗伯特算子、索伯尔算子、canny算子、拉普拉斯算子，分别进行边缘检测。 具体见说明文档。(A given image is processed by median filter. Robert operator, Sobel operator, Canny operator and Laplace operator are used for edge detection. See the instruction document for details.)

数字图像处理(Digital Image Processing)是通过计算机对图像进行去除噪声、增强、复原、分割、提取特征等处理的方法和技术。 [1] 数字图像处理的产生和迅速发展主要受三个因素的影响：一是计算机的发展；二是数学的发展（特别是离散数学理论的创立和完善）;三是广泛的农牧业、林业、环境、军事、工业和医学等方面的应用需求的增长(Digital Image Processing (DIP) is a method and technology of removing noise, enhancing, restoring, segmenting and extracting features from images by computer. [1] The emergence and rapid development of digital image processing are mainly influenced by three factors: first, the development of computer; second, the development of mathematics (especially the establishment and improvement of discrete mathematics theory); third, the growth of the demand for extensive applications in agriculture, animal husbandry, forestry, environment, military, industry and medicine.)

delaunay三角化程序 delaunay三角化程序 delaunay三角化程序(delaunay triangulation delaunay triangulation process procedures delaunay triangulation process)

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 )