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c++特征提取，提取图像当中的红色灯笼。。。(c++ feature extraction, image extraction among red lanterns)

由VC实现画矩形、椭圆和随手画功能，对图像处理人员会有帮助(paintings by VC rectangular, oval and hand painting functions, image processing staff to be helpful)

分水岭算法的实现,用VC++语言实现，构成可靠的算法实现(the implement of the watershed)

在图像的DCT系数上嵌入信息，图像为常见的512*512大小的灰度图（实验所用图像为LENA.BMP）。嵌入的信息为一二进制Logo图（实验所用logo图为tj-logo.bmp），该图大小为32*32，共1024个Bit。 1. 在LENA图中嵌入水印，输出嵌入后的水印图像。 2. 对水印图像解码，输出解码后得到的logo图，并统计错误率。 3. 使用不同的嵌入强度进行嵌入，观察其对作品直觉效果和解码效果的影响，绘制相应的曲线。 4. 使用加入噪声、改变对比度、JPEG压缩等攻击方法对水印作品进行攻击，查看解码的效果。 (Information embedded in the DCT coefficients of the image, the image of the common 512* 512 size gray-scale (experimental image LENA.BMP). Information embedded in a binary Logo Figure (used in the experiment logo picture shows the tj-logo.bmp), the plot size 32* 32, 1024 Bit. LENA Figure embedded watermark, the watermark image output embedded. (2) logo watermark image decoding, the output decoded Figure statistical error rate. (3) using a different embedding strength for embedding, observe the works intuitive effects and decoding results, and draw the corresponding curve. (4) by adding the noise, change the contrast, JPEG compression attack methods to attack, to see the effect of decoding the watermark works.)

利用Visual C++实现AVI文件的图像截取 实现对图像数据的读取显示 实现视频图像处理技术 编程中如何操作数据库中的图像字段 实现数字图像增强处理(Use Visual C++ AVI file image interception To read the image data display Video image processing technology Programming how to operate the database image field Digital image enhancement)

说明：  对图像进行中值滤波，去除噪声，并与原图像进行比较(Median filter on the image to remove noise, compared with the original image)

通过GDAL读取常用遥感影像，如img，tiff，可实现读取显示和雷达影像处理的一些基本算法(Read through GDAL common remote sensing images, such as img, tiff, read the display and radar can achieve some of the basic image processing algorithms)

自动匹配下拉列表框中的内容,根据所选下拉列表框的不同去加载不同的名片(Automatic matching of the drop-down list box in the content, according to the selected drop-down list box is different to load a different card )

在VC6.0环境下，借助openCV函数库，对视频中的人脸进行检测，并实时跟踪，然后用Haar特征的分类器定位人脸，并检测瞳孔存在与否，提取关于眼睛的疲劳信息(In VC6.0 environment, with the aid of openCV function library, to detect human faces in video, and real-time tracking, positioning and use characteristics of Haar classifier faces, and examine the pupil existence, to extract the information about the fatigue of the eye)

人头检测 通过颜色分割产生人头头发部分的二值图像，计算此部分的面积和长宽比来判断是否有人头(human detection)