(ok)NHLIScode

基于区域增长对图像进行分割，得到感兴趣区域(Sengment image based on the regiongrowing.)

Digital Image Processing writed by Gonzalez second edition of the Chinese version

基于Hog特征 SVM分类器，利用Opencv3.0进行手写数字识别的源代码及所需资源文件（训练图片、测试图片）

几个图像中嵌入文本的LSB信息隐藏算法，适合信息隐藏初学者,注释详细(Several images embedded in the text of the LSB Information Hiding Algorithm for Information Hiding beginners, notes in detail)

混合高斯分布EM算法，可以算混合高斯分布的三个参数。混合高斯分布更接近系数分布。(mixed Gaussian distribution EM algorithm can calculate mixed Gaussian distribution of the three parameters. Mixed closer to the Gaussian distribution coefficient.)

说明：  图像分割代码，c++实现(Image segmentation code, c++ Achieve)

为了提高数字图像中椭圆检测的效率和准确性,提出了一个基于最小二乘法的改进的随机椭圆检测算法. 该算法随机选取图像中的3 个边缘点,在以这3 个点为中心的窗口内,从边缘点中拟合出可能椭圆,并通过随机选 取的第4 个边缘点来确认可能椭圆. 利用直接最小二乘法椭圆拟合的特性,引入可能椭圆边缘点收集和椭圆重新 拟合的迭代过程来提取最终的椭圆参数. 通过对含有不同噪声的仿真图片和包括残缺椭圆的实际图片的实验表 明,新算法的改进是有效的. 与原算法相比,新算法降低了对参数的依赖性,提高了检测的速度、稳定性和准确性, 同时保留了原算法的抗噪声能力.(: An imp roved randomized ellip se detection algorit hm based on least square approach was proposed to enhance t he efficiency and accuracy of ellip se detection in digital images. This algorit hm randomly se2 lect s three edge point s in t he image , and t hen uses least square approach to fit all t he edge point s in three windows , which are defined by t he t hree edge point s. The forth edge point is randomly selected to judge whet her a possible ellip se exist s in t he image. Utilizing the characteristic of direct least square fit ting of ellip se , an iteration process of edge point collecting and ellip se refit ting of possible ellip se was int roduced to ext ract t he final ellip se’s parameters. Artificial images wit h different level s of noise and nature images containing incomplete ellip ses were employed to test t his algorithm. Experimental result s show that t he improvement s are notable. Compared with the original algorit hm , t he propo sed algorit hm reduces)

FSIM图像质量评价性能指标算法，衡量图像质量好坏程度(FSIM image quality uation performance index algorithm, to measure the degree of image quality )

sample illust back image2 mask sample

利用MATLAB的图像用户界面GUI设计一个简单的菜单式图像处理系统。通过该程序实现对图像的简单处理、变换和去噪等功能，满足课程设计的要求。(A simple menu image processing system is designed by using the image user interface GUI of MATLAB. Through this program, the functions of image processing, transformation and denoising are realized, which meet the requirements of curriculum design.)