KMeans-with-opencv

混合高斯(Mixture of Gaussian, MOG) 背景建模算法和Codebook 背景建模算法被广泛应用于监控视频的运动目标检测问题, 但混合高斯的球体模型通常假设RGB 三个分量是独立的, Codebook 的圆柱体模型假设背景像素值在圆柱体内均匀分布且背景亮度值变化方向指向坐标原点, 这些假设使得模型对背景的描述能力下降. 本文提出了一种椭球体背景模型, 该模型克服了混合高斯球体模型和Codebook 圆柱体模型假设的局限性, 同时利用主成分分析(Principal components analysis, PCA) 方法来刻画椭球体背景模型, 提出了一种基于主成分分析的Codebook 背景建模算法. 实验表明, 本文算法不仅能够更准确地描述背景像素值在RGB 空间中的分布特征, 而且具有良好的鲁棒性.(The background modeling algorithm of mixture of Gaussian (MOG) and codebook is widely used in moving object detection of surveillance video. However, the ball model of MOG usually assumes that the three components of RGB are independent, while the cylinder model of codebook assumes that the value of background pixel is distributed uniformly within the cylinder and the changing direction of brightness points to the origin of the coordinate system. These assumptions reduce the descriptive capability for background modeling. Therefore, the paper proposes an ellipsoid- based background model, which overcomes the MOG and codebook0s limitations. By using principal component analysis to depict the ellipsoid background model, a novel PCA-based codebook background modeling algorithm is proposed. Experiments show that this algorithm can not only give more accurate description of the distribution of background pixels but also have a better robustness.)

图像增强，包括图像的平滑、锐化、边缘识别等操作(Image enhancement, including image smoothing, sharpening, edge detection and other operations)

常用数字图像处理，图像变换等功能的实现，锐化平滑等算法(digital image processing)

源码包括了常用的图像处理方法，代码详细，适合初学者(Source code, including the commonly used image processing method, the code in detail, suitable for beginners)

数字图像处理第二版英文版（冈萨雷斯）.pdf(Digital Image Processing Second Edition English (Gonzalez). Pdf)

实现bmp位图的图像放大缩小，包含整个mfc的源码文件。(Achieve bmp bitmap image zoom, contains the entire mfc source files.)

MRF代码实现,visual C++ 代码，不错，可以尝试(an implementation of MRF)

说明：  傅立叶变换在图像处理中的重要作用： (A) 图像增强与图像去噪 绝大部分噪音都是图像的高频分量，通过低通滤波器来滤除高频噪声；边缘也是图像的高频分量，可以通过添加高频分量来增强原始图像的边缘； (B) 图像分割与边缘检测 提取图像高频分量 (C) 图像特征提取 形状特征：傅里叶描述子 纹理特征：直接通过傅里叶系数来计算纹理特征 其他特征：将提取的特征值进行傅里叶变换来使特征具有平移、伸缩、旋转不变性 (D ) 图像压缩 可以直接通过傅里叶系数来压缩数据；常用的离散余弦变换是傅立叶变换的实变换； (Fourier transform in the important role of image processing: (A) image enhancement and image denoising Most of all images of high frequency noise by low pass filter to filter out high frequency noise edge is the image of the high frequency components can be enhanced by adding high frequency components to the edge of the original image (B) Image segmentation and edge detection High frequency components extracted image (C) image feature extraction Shape features: Fourier descriptors Texture: directly through the Fourier coefficients to calculate the texture features Other features: The characteristic value extracted by Fourier transform to the characteristics of translation, scaling, rotation invariance (D) image compression Fourier coefficients can be directly compressed data commonly used discrete cosine transform is the Fourier transform of the real transformation 朗读显示对应的拉丁字符的拼音)

说明：  ：针对显微图像分析、识别需要的全自动控制显微镜，研究开发其相应的图像处理算法。提 出了能量谱自动聚焦评价函数算法、自适应选取基准图的图像拼接算法、改进 Laplacian算子的多层 聚焦图像叠合算法等。该算法模块已成功地应用于所开发的CMIAS 显微医学图像分析系统中，取得 了满意的应用效果。(【ABSTRACT】For the automatic microscope required by micro-image analysis and recognition, the relevant image processing a lgorithms are investigated. Three algorithms are described: energy-spectrum image auto focusing evaluation function, image merging based on the adaptive selection of standard image and sum-modified-Laplacian (SML) operator for multi-focus image fusion. The algorithms have been applied successfully to CMIAS medical micro-optical image analysis system and testified to be feasible and effective. )

人脸检测：可自动检测人脸，速度还可以吧！(Face Detection : can automatically detect faces and can also speed!)