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SUSAN A New Approach to Low Level Image Processing
- 用于图象边缘的精确检测的susan算法的文章- Uses in the image edge precise examination susan algorithm article
SDL-1.2.9
- This the Simple DirectMedia Layer, a general API that provides low level access to audio, keyboard, mouse, joystick, 3D hardware via OpenGL, and 2D framebuffer across multiple platforms. -This the Simple DirectMedia Layer. a general API that pr
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- 图像分割是图像处理与计算机视觉领域低层次视觉中最为基础和重要的领域之一，它是对图像进行视觉分析和模式识别的基本前提．阈值法是一种传统的图像分割方法，因其实现简单、计算量小、性能较稳定而成为图像分割中最基本和应用最广泛的分割技术．-image segmentation is image processing and computer vision field of low-level visual basic and the most important one of the fields, It
sltoolbox_r101
- sltoolbox (Statistical Learning Toolbox) organizes a comprehensive set of matlab codes in statistical learning, pattern recognition and computer vision. It includes 256 m-files in 24 categories, which are from low-level computational routines to high
gcrf_demo
- This MATLAB code is an example of how to train the GCRF model described in \"Learning Gaussian Conditional Random Fields for Low-Level Vision\" by M.F. Tappen, C. Liu, E.H. Adelson, and W.T. Freeman in CVPR 2007. If you use this code in your re
用MATLAB绘制低阶的平板波导的色散曲线图
- 用MATLAB绘制低阶的平板波导的色散曲线图,MATLAB drawn by low-level slab waveguide dispersion curves
blepo_0.6.4.zip
- Blepo is an open-source C/C++ library to facilitate computer vision research and education. Its goals are threefold: to enable researchers to focus on algorithm development rather than low-level details such as memory management, reading/writing f
abi_SystemV
- system v ABI 2007 amd64 平台架构的实现 介绍了low level，obj，lib，ddl的原理-system v ABI 2007 amd64 arch，low level，obj，lib，ddl implementation
CNNfeatureextraction
- 提出了一种基于目标边界的不变特征提取方法。导出了用物体角点坐标表示的低阶边界矩的闭合形式，构造了 基于边界矩的仿射变换不变量。该方法只需要对物体角点进行简单的代数运算，因此，该方法简单明了，计算量很小。实 验结果证明了该方法的有效性-A goal of the border based on the same feature extraction method. Exporting objects with corner coordinates of the low-level clos
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- 计算机图像处理系统从系统层次上可分为高、中、低档三个层次，目前一般比较普及的是低档次的系统，该系统由CCD（摄像头）、图像采集卡、计算机三个部分组成，其结构简单，应用方便，效果也比较不错，得到的图像较清晰。目前网上基于VC开发经验的文章不少，可是关于如何在VC开发平台上使用图像采集卡的文章确没发现，笔者针对在科研开发中积累的使用图像采集卡经验，介绍如何自己是如何将采集卡集成到图像开发系统中，希望能够给目前正需要利用图像采集卡开发自己的图像处理系统的朋友有所帮助。-Computer image p
JPEG
- Here is a quite detailed low level design document for the Core: Low Level Design Document for JPEG Encoder
geom2d
- Library to handle and visualize geometric primitives such as points, lines, circles and ellipses, polygons... The goal is to provide a low-level library for manipulating geometrical primitives, making easier the development of more comp
libcvd-20090828.tar
- libCVD is a very portable and high performance C++ library for computer vision, image, and video processing. The emphasis on providing simple and efficient image and video handling and high quality implementations of common low-level image processing
MATLAB_Medical_Image_Process_Experiments
- MATLAB医学影像处理实验(内含14个原代码及教学的说明) (1)Plot a sine function using MATLAB, and write the data into a file (2)Read data from a file, plot a SINC function, and append the result back to the same file (3)Plot a Gaussian distribution using MATLAB (4)Fo
Low-levelOpenGLshadinglanguageandtheHighLevelShade
- OpenGL 低级着色语言与高级着色语言-Low-level OpenGL shading language and the High Level Shader Language
SUSAN
- SUSAN角点检测算法经典文献 This paper describes a new approach to low level image processing in particular, edge and corner detection and structure preserving noise reduction. Non-linear filtering is used to define which parts of the image are closely rel
SURF
- SURF角点检测 This paper describes a new approach to low level image processing in particular, edge and corner detection and structure preserving noise reduction. Non-linear filtering is used to define which parts of the image are closely related to
fgbfdgh
- 基于结构信息提取的图像质量评价构相似性理论是一种关于图像质量评价的新思想．与自底向上地模拟人眼视觉系统(HVS)低阶的组 成结构不同，结构相似性理论自顶向下地模拟HVS的整体功能．-Theory is a kind of image quality evaluation about the new thoughts. And the simulation of human visual system (HVS) low-level group Into different structu
mainHarris
- Harris/Plessey Operator Introduction This operator was developed by Chris Harris and Mike Stephens in 1988 [3] as a low-level processing step to aid researchers trying to build interpretations of a robot s environment based on image sequences