ostu

利用VTK实现图像的放大缩小，基于对话框编写的，有助于学习VTK的朋友(Using VTK to achieve the image to zoom in, based on the dialog box, prepared to help a friend learn VTK)

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)

对图像进行平滑去噪，提高图像的质量，为后期的图像处理打基础(very good)

说明：  用于物体目标轮廓的提取与跟踪，能更好的识别出物体轮廓。(Target contour for object extraction and tracking, to better identify the contours of objects.)

对图像进行平滑处理，像各种滤波的方法，如均值滤波法、中值滤波法(Smoothing the image, like the various filtering methods, such as mean filtering, median filtering method)

N年前上数字图像课时写的实验报告和程序，用滤波反投影（Filter Back Project，FBP)法重建图像。(Report and source code for data image restore experiment, using FBP.)

2011年比较流行的简单快速的运动目标检测代码。(More popular in 2011, a simple and rapid moving target detection code.)

我改写后的graphbrian类，原本支持柱状图饼图和折线图的，现在添加了对这些图的风格调整，主要是增加了调整绘图区背景色和文本背景的功能，还增加了把图片保存为bmp文件的功能，以便用其他软件方便的打印。(I would then graphbrian category, which originally supported the pie chart histogram and line graph, and now added to adjust the style of these plans, the main adjustment is to increase the drawing area background color and text background function, but also an increase of the picture saved as bmp files, in order to use other software to facilitate printing.)

摘　要:舌象中的裂纹是中医舌诊中的重要内容。由于拍摄条件的不同,舌象质量有较大差异,传统的阈值选取方法并不 适用。文中提出一种舌象裂纹检测的自适应阈值选择方法。该方法利用舌象的L 3 a 3 b 色彩特征及区域的分裂- 合并, 对舌象进行区域分割,自适应地选取舌中部区域的色彩值作为阈值,对整个舌象进行裂纹提取。经验证,本方案对不同的 舌象能较好地提取出裂纹,实现舌象裂纹诊断的客观化。(Tongue’ s crack is a very important part of herbalist doctor diagnosis. For the different screen conditions , there are many differ2 ences on the tongue’ s quality. It is not effective to use the t raditional threshold ext raction algorithm. In order to solve this problem , pro2 pose a new adaptive threshold algorithm. Present the segmentation of the image of tongue by using the feature on tongue in the L 3 a 3 b color space and the split- combining algorithm. Then use the threshold , which is the color value ext racted automatically in the middle of the tongue , to detect the crack of the whole tongue. The experiments show that this approach is able to distill the crack effectively to different tongue images , and achieve the objectivity of the diagnosis based on the tongue’ s crack.)

说明：  转载的，通过眨眼前后灰度图对比是别人眼，一个学习opencv工具的好例程。(Reproduced by blinking eyes of others around the grayscale contrast, a learning tool opencv good routine.)