北京大学遥感所的研究生图像处理讲义高级遥感数字图像处理（硕士生课程）之第十三章 离散图象变换...

基于BP神经网络对印刷体字符图象进行识别,经过前期处理,获得64*64的二值图象,其二值图象数据作为神经网络的输入.-BP neural network based on the characters of the print images to identify, after pre-treatment, access to 64* 64 binary image, and the second value of image data as the neural network input.

purpose applies mean filter to gray-scale PGM image compile gcc -g -o mean_pgm mean_pgm.c -lpgm -lpbm -lm -purpose mean filter applies to gray-scale PGM image compile gcc-g-o mean_pgm mean_pgm.c- lpgm- lpbm- lm

划线，画园和画矩形等window系统实现的步骤-draw line

spineline object 3d rotation viewer

understanding the davinci resizer -understanding the davinci resizer

svga图形编程库，适用DOS,borlandc 3.1 turbo c, MS-C.可实现 256色以上编程-svga graphics programming library, application DOS, borlandc 3.1 turbo c, MS-C. Color can achieve more than 256 programming

产生水纹、火焰及熔岩效果示例,本程序可以在图像上生成特效效果，值的一下。-Generated水纹, flame and lava sample effect, the program can generate effects in the image effect, the value of the click.

一个vb编的二维图形引擎-a vb series of the two-dimensional graphics engine

医学图像三维重构平台 mitk 开发指南-3D Medical Image Reconstruction platform mitk Development Guide

提出一种新的非线性变换的彩色空间 ″″, 利用次高斯概率分布函数拟合皮肤色度信息, 得到候选区 YC C r b 域。为了排除候选区域中的非人脸, 首先根据均值和方差信息分割出候选区域中的纹理特征信息, 再通过多尺度 ) ( 信息定位眼睛, 然后根据人脸特征的几 形态边缘检测算子检测候选区域的边缘, 利用 边缘方向 PCA PCAED ( ) 何形状信息定位其他特征 鼻、嘴 , 通过这些几何特征信息对肤色分割得到的候选区域进行验证, 最终得到正确 的人脸区域。利用3 个实验数据集测试该算法, 并与其它相应的算法相比较, 提出的非线性彩色空间对于肤色分 割具有很好的效果, 且对光照和姿态具有良好的不变性。另外, 利用 信息和几何特征信息检测人脸特征 PCAED 具有很高的定位精度, 定位检测率优于其他方法。实验结果表明, 该算法具有定位准确率高, 漏检率和误检率低 等特点。- A novel approach for skin segmentation and facial feature extraction is proposed The proposed skin segmentation is a method for integrating the chrominance components of ″″ . ″″ r b r b nonlinear YC C color model The chrominance components of nonlinear YC C color space , are modeled using a subgaussian probability density function and then the face skin is seg . , mented based on this function In order to authenticate the face candidate regions firstly tex ture information in face candidate regions is segmented using mean and variance of luminance ,