资源列表
adaptive_anisotropic_2D_gaussian_filter
- Gaussian filtering in one, two or three dimensions is among the most commonly needed tasks in signal and image processing. Finite impulse response filters in the time domain with Gaussian masks are easy to implement in either floating or fixe
video2
- opencv的运用，在初学的可以参考，对视频和摄像头的调用-opencv the use of the beginner' s to refer to the video and camera calls
New-Text-Document-(4)
- 通过定义曲面和均匀网格绘制一个具有光照和明暗处理效果的Bezier曲面（图1）的部分主要代码： -Bezier
A-new-adaptive-median-filter
- 一种新的自适应中值滤波方法。将3 x3窗口中心的极值点作为候选噪声点，若候选噪声点仍然是7 x7窗口的极值点，则该点即是噪声点。若以噪声点为中心的3 x3滤波窗口的中值不是噪声，则噪声用中值替换。重复以上过程，直到没有噪声点被替换。如果图像中仍然存在人的噪声团块，则噪声用相邻的三个信号点的灰度均值替换。实验结果表明，该方法能够有效去除脉冲噪声，并在抑制噪声的同时很好地保护图像的细节。-A new adaptive median filter. The extreme points of the
BresenhamLine
- Bresenham画线算法程序： 用一个坐标轴来当步长值(即+1)，另一个坐标轴是否加1则跟据斜率(k)来确定，K 如果大于0.5，那么也加+1，如果小于0.5那么即不变。为了方便计算，如果d大于1 ，那么就减一，归0。可设e,e=d-0.5，于是就有e>0时，加1，e<0时不变，这样便 于硬件实现。-Bresenham
tux
- 计算机图形学 黑色正方体在红光照射下旋转-Graphics rotating cube
xinxinengliang
- 基于信息能量的直方图均衡化算法,在传统的直方图均衡化算法上的改进，对图像质量的改善效果很明显。-Histogram equalization method based on the information on the energy, the improvement on the traditional histogram equalization algorithm on the image quality improving effect is obvious.
testface
- 基于K-L展开的人脸检测matlab程序，采用K-L展开对图片主成分分析、多图训练，从而达到在复杂图片中检测人脸的功能。-KL expansion based on face detection matlab program, using KL expansion of the picture principal component analysis, multi-map training, so as to achieve a complex picture face detection fu
chepaitiqu
- 这组代码能够提取出交通视频中帧图像中汽车的车牌，能够独立的检测分割显示出车牌，对于车牌识别有很大的帮助。-This set of code to extract the traffic video frame image of car license plate, can the independent testing shows the license plate, segmentation is of great help for the license plate recognition.
skindetection
- 基于光谱的人脸肤色检测,修改参数后，可用于色彩检测-Face detection based on skin color spectrum.
SobelOperator
- 在C++中使用sobel算子对图像进行距离变换-Use the sobel operator in C++ distance transformation in the image
decision-tree
- 二叉决策树能很好地运行，适合初学者,希望能帮助大家更好地学习算法-Binary decision tree can run well, suitable for beginnersHope I can help you better learning algorithm