dakai

本代码实现的功能：24位位图（BMP）的灰度化。具体实现过程：打开图像文件,找到数据区(每3个字节代表一个象素的R,G,B值),循环扫描,根据RGB的权重,计算出灰度值. 如果要得到256色灰度图,则要新建一个调色板,修改信息头和文件头.(Realize the function of the code: 24-bit bitmap (BMP) of the gray. Concrete realization of the process: Open the image file, locate the data area (3 bytes per pixel on behalf of a R, G, B values), cyclic scan, according to the weight of RGB, gray value is calculated. If you want to get 256 colors grayscale, would create a new palette, modify the header and file header information.)

canny边缘检测（自动设置Sigma的高斯平滑+Sobel(原始)+自适应直方图阈值）(canny edge detection (automatically set Sigma Gaussian smoothing+ Sobel (original)+ adaptive histogram threshold))

基于efficient subwindow search算法的windows实现(efficient subwindow search for windows )

将一个图像的感兴趣区域替换到另一张图像的相同区域中(Will replace the region of interest of an image to another image of the same region of the)

精通Visual C++图像处理编程中的一个小程序，实现图像的各种扫描和移动，百叶窗等，可以作为初学者学习用

对圆形，正方形，长方形等几何图形进行计算面积，周长等运算(Circular, square, rectangular and other geometric shapes are calculated area, perimeter of operation)

Abstract—Noninvasive ultrasound imaging of carotid plaques allows for the development of plaque-image analysis methods associated with the risk of stroke. This paper presents several plaqueimage analysis methods that have been developed over the past years. The paper begins with a review of clinical methods for visual classification that have led to standardized methods for image acquisition, describes methods for image segmentation and denoizing, and provides an overview of the several texture-feature extraction and classification methods that have been applied. We provide a summary of emerging trends in 3-D imaging methods and plaque-motion analysis. Finally, we provide a discussion of the emerging trends and future directions in our concluding remarks.

图像球面化，对于输入的图片进行球面变换达到图形变形的效果(Spherical image of, for input images to spherical transformation to achieve the effect of graph distortion)

该源码为目标检测和跟踪算法 包括： 1. 静态背景下的背景预测法目标检测 2. 静态背景下帧间差分法目标检测 3. Mean Shift目标跟踪方法 4. 重心多目标跟踪方法 (The source code for target detection and tracking algorithm include: 1 Static background background prediction target detection 2 Static background frame difference method for target detection 3. Mean Shift tracking method 4 multi-target tracking methods focus)

是关于图像的基础操作，包括图像倾斜矫正，图像增强，去除噪声，图像压缩等技术(It is on the image on the basis of operations, including image tilt correction, image enhancement, noise removal, image compression technology)