资源列表
GaussianMixtureModel
- GMM(Gaussion Mixture Model) ,从matlab 主站获得的程序，本人已测试-Gaussion Mixture Model is down load from matlab net
Cross-Correlation-Target-Image-Detection
- 正交相关目标检测，采用正交相关方法检测指定目标在图像中的位置。适用于计算机视觉中的视频目标检测、视觉目标检测、目标定位、视觉目标跟踪、视频目标跟踪、图像匹配、图像配准等工作。-cross relation detection is used to detect object in image for in the field computer vision such as visual object detection, motion detection, object localization
susan2l
- image processing (About corner detection)
EM_GM
- EM算法实现,是matlab主站上获得的可靠程序。-EM algorithm，which is from the matlab net about image processing.
openglfk
- opengl 实现拾取与反馈，可以获得三维窗口中的任意点的三维坐标。-pick-up and feedback to achieve opengl obtain three-dimensional window of three-dimensional coordinates of any point.
H261coding
- H.261编码格式提出于1990年，用于运动图像的编码中。它的编码效率高，图像质量好且实时性好，广泛用于会议系统的运动图像编码之中。-H.261 encoding format proposed in 1990, for the coding of moving picture. Its high coding efficiency, image quality and real-time, and conferencing systems are widely used in image co
mpegprocessing
- 通过实验了解Mpeg1协议中的B帧编码方法以及Mpeg2协议P帧-帧场自适应预测编码-Mpeg1 agreement through experiments to understand the B-frame encoding method and the P frame Mpeg2 Agreement- Adaptive predictive coding frame field
1
- #基于纹理的图像检索,使用两种方法_局部边缘直方图,改进边缘直方图-# Based on the texture image retrieval, the use of two methods of local edge histogram _ to improve the edge histogram
freemorphing21
- Free Morphing creates a sequence of frames which are the transformation of the source image to target image, giving the appearance that the source image "becomes" the target.
3DTF
- 一篇国外人写的地形跟随的文章，最优3D实时地形跟随和威胁回避。-Written by a foreign person to follow the topography of the articles, the best 3D real-time threat avoidance and terrain following.
Pictureprocess
- 图形图像的处理操作，界面比较漂亮，功能比较强大，可以作为学习的例子-Graphic image processing operations, the interface more beautiful, more powerful features can be used as examples of learning
22222
- 面向微电子制造的机器视觉辅助元件检测研究,介绍了视觉识别电子元器件的方法！-Microelectronics for the manufacture of machine components detection of visual aids to introduce the visual approach to identify electronic components!