图像的增强 模板操作 中值滤波 梯度锐化 伪彩色编码

全自动CAMSHIFT算法 全自动CAMSHIFT算法 全自动CAMSHIFT算法-CAMSHIFT automatic algorithm CAMSHIFT automatic algorithm CAMSHIFT automatic algorithm

程序代码说明 P0701：细胞边缘检测 P0702：癌细胞形态学分析 P0703：癌细胞颜色分析-Procedure Code Description P0701: cell edge detection P0702: morphological analysis of cancer cells P0703: color analysis of cancer cells

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 c

图像增强（基于利用模板操作的平滑处理，中值滤波处理）-Image enhancement (based on the use of templates smoothing operations, median filtering treatment)

SIFT特征点检测算法是一种有效的图像特征检测法，对旋转、尺度，光照变化都具有一定的鲁棒性。-SIFT feature detection algorithm is an effective method of image features, rotate, scale, the light changes robustness。

利用灰度图 建共生矩阵 利用特征值 对纹理图想分割-The use of grayscale co-occurrence matrix to build the use of characteristic values of the texture map would like to partition

马尔科夫vc源代码，偶找了很久才发现的，应用在图像处理中，强烈推荐-Markov vc source code, even for a long time only to find that the application of the image processing and strongly recommended

Coin Detection using Hough Transform

基于结构特征的虹膜识别源码　vc++。 － -based on the structural characteristics of the iris identification source vc.-