资源列表
exp01
- 1.运用Laplacian算子，基于二阶微分的图像增强，即拉氏变换法进行图像平滑 2.利用邻域平均法实现图像的平滑处理 3.利用Robert算子做锐化处理-1. The use of Laplacian operator, based on second-order differential of the image enhancement, that is, Laplace transform method for image smoothing 2. The use of neigh
ladder_pass
- matlab编写的梯形低通滤波器对与图像的影响，画图比较滤波前后的对比图。-the preparation of matlab trapezoidal low-pass filter and image of the effect of drawing the contrast to compare before and after filtering Fig.
ABdemo
- 下载别人的基于 AdaBoost 人脸检测源代码 供大家一起学习-Download others AdaBoost-based face detection source code for everyone to learn
txrh
- 实现了图像的抠像和填充，并可实现多幅图像的融合。-Keying to achieve the image and fill, and to achieve the integration of multiple images.
Wavelet
- 利用VC++实现基于小波变换的图像拼接，使用模板匹配法-Wavelet match
libMesaSRtester
- SwissRanger的测试程序。 不知道国内有没有人使用这个东西。 有的话欢迎交流。-The test program of SwissRanger.
Find_Lips_in_YCbCr
- 在YCbCr通道上，对人的嘴唇的寻找，通过大量数据样本得到的嘴唇颜色区域，效果不错，这个程序只是在静态图片里寻找，对做嘴形识别的人有帮助-Channel in the YCbCr on the lips of people search through a large amount of data samples to be the color of the lip region, the effect is true that this procedure only to find a sta
Image
- a very good dll for image process, provide the method to measure and caculate the image, circle fitting, pattern match, ....and so on
ImgCluster
- vc++6.0+gdal开发的聚类算法的COM组件，可在vb或.Net中直接调用。其中包含的聚类算法有：K-Means,ISODATA等,可对Image影像进行聚类处理。-vc++6.0 development of COM components clustering algorithm can vb or. Net direct call. Which includes the clustering algorithm are: K-Means, ISODATA, etc.
Regional
- 区域法立体匹配的实时性问题研究立体视觉匹配的相关算法-Regional real-time stereo matching method of study related to stereo vision matching algorithm
image_demo
- 使用vc++2005完成,实现B样条曲线拟合曲线.单文档视图结构.可打开显示图片,可使用B样条曲线对对象轮廓进行拟合.显示B样条曲线的次数,控制点个数,控制点坐标,节点向量等-Using vc++2005 completed, the realization of B-spline curve fitting. The structure of a single document view. To open the display picture, you can use B-spline cu
iris_detection
- 识别虹膜和眼毛位置程序。使用方法： 1.载入眼睛图片。 2. 定位实验->虹膜定位：确定虹膜圆心，以及虹膜内外环半径。 3. 定位实验->眼毛检测：结果为两条圆心为端点的折线段，标明没有眼毛的虹膜区域。-Identify iris and eye hair location. Use: 1. Loading eye picture. 2. Positioning Experimental->Iris Location: identification of the i