RayTracer

说明：  缺陷检测，定位缺陷位置。主要用于工业之中螺帽的螺纹线的检测(Defect detection, location of defect location. Detection of screw thread for nuts in industry)

图形voronoi图的自动生成算法，用vc做，是基于一般图形voronoi图的算法，结合数字图形处理里的轮廓跟踪算法，使一般图形voronoi图能够根据不同的生成元总动生成。(Graph voronoi diagram automatic generation algorithm, using vc do is based on the general graph voronoi diagram algorithm, combined with digital image processing in the contour tracking algorithm, the general graph voronoi diagram to the total depending on the generator automatically generated.)

利用OpenCV实现单幅图片对于手指的精确识别(Single image using OpenCV to achieve precise identification of the finger)

说明：  fluent udf dpm particle diamter

生成avi视频截图序列。设置截图时长，截图频率，截图类型的参数。(Generate avi video sampling sequence.Screenshot duration, frequency and types of parameters are allowed to set freedom.)

说明：  VC的一些工程案例，包括车牌识别，人脸识别，图像处理基本操作等(car license recognization system)

特征点匹配时，采用构造KD-tree，用最优节点优先法寻找最佳匹配点(Matching feature points, the tectonic KD-tree, with the optimal node is preferred method to search for the optimal matching point)

特征提取中利用小波边缘检测C++源码，希望对大家有用，而且偶也能下载程序了，(feature extraction using wavelet edge detection C source code, we hope to useful, but can even download, Ha ha)

GDAL影像显示 建立金字塔通过i移动图像 进行图像的放大缩小 多波段显示影像金子塔显示 (GDAL image creates pyramid)

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.)