AIM

Viola-Jones Fast Face Detection的matlab实现。(Viola-Jones Fast Face Detection Mex Implementation)

程序代码说明 P0401：用Prewitt算子检测图像的边缘 P0402：用不同σ值的LoG算子检测图像的边缘 P0403：用Canny算子检测图像的边缘 P0404：图像的阈值分割 P0405：用水线阈值法分割图像 P0406：对矩阵进行四叉树分解 P0407：将图像分为文字和非文字的两个类别 P0408：形态学梯度检测二值图像的边缘 P0409：形态学实例——从PCB图像中删除所有电流线，仅保留芯片对象(Program code description P0401: Detects the edge of an image with the Prewitt operator P0402: LoG operator with different σ values is used to detect the edge of the image P0403: Detects the edge of an image with the Canny operator P0404: Threshold segmentation of the image P0405: Image segmentation using watermark threshold method P0406: Quadtree decomposition of the matrix P0407: The image is divided into text and non-text of the two categories P0408: Morphological gradient detects the edge of a binary image P0409: Morphology Example- Deletes all current lines the PCB image, leaving only the chip object)

加权对等间隔线阵指向性的影响（切比雪夫加权获得等高度旁瓣，获得最窄主瓣）(The influence of weighted peer spacing array directivity (Chebyshev weighted obtains equal height sidelobe and obtains the narrowest main lobe).)

说明：  实现了平移、缩放、旋转和错切等仿射变换的问题，并用MATLAB逼真模拟了蕨类叶、变形蕨类叶与拟仿射变换分形图。(Achieved a pan, zoom, rotate and cross cutting issues such as affine transformations, and use MATLAB to simulate real fern leaf, fern leaves and to be deformed affine fractal images.)

针对传统中值滤波算法的优缺点,提出了一种基于相似度函数的自适应加权中值滤波算法.(Abstract：According to excellence and shortcoming of conventional median filter algorithm，an algorithm called adaptive weighted median filter algorithm based on similarity function is proposed)

说明：  矩阵填充经典算法的代码，包含SET，SVT等(Matrix filling code of classical algorithm, including set, SVT, etc)

用奇异值分解的方法实现图像压缩，有助于初学者了解奇异值分解的应用(Using singular value decomposition method to achieve image compression will help beginners understand the application of singular value decomposition)

本程序用C语言在LSB上添加水印。最低有效位(LSB)是给这些单元值的一个二进制整数位位置，就是，决定是否这个数字是偶数或奇数。LSB有时候是指最右边的位，因为写较不重要的数字到右边位置符号的协定。它类似于一个十进制整数的最不重要的数字，它是在一个(最右边)位置的数字。(This program in C language to add a watermark on the LSB. The least significant bit (LSB) is a binary integer position to the value of these units, that is, to decide whether this number is even or odd. LSB is sometimes referred to as the rightmost bit, write a less important figure to the right location symbol Agreement. It is similar to the most significant digit of a decimal integer, it is the number in a (far right) position.)

使用K-means聚类算法的改进算法K-means++对图像区域进行分割。(using the improved algorithm K-means++ segment image.)

说明：  图像处理的位图操作，256色转为灰度图，图像处理入门源程序(Bitmap image processing operations, 256-color to grayscale, image processing, entry-source)