graphics operations, graphic output, image transformation, besier curve

一系列简单实用的图像处理源代码-a series of simple and practical image processing source code

1024点fft程序，在ccs上可以直接仿真，无需调试-1,024 points fft procedures, the ccs can direct simulation, debugging without

数字图像处理,离散余弦dct变换域中水印的提取-digital image processing, discrete cosine transform domain Extra watermark extraction

H.264的解码器 输出文件格式为yuv 开发工具Visual Studio 6.0 以上-H.264 decoder output file format yuv development tools for Visual Studio 6.0 and above

是腐蚀，膨胀，细化算法 命令行编译过程如下 vcvars32 rc bmp.rc cl morph.c bmp.res user32.lib gdi32.lib 注意事项： 运行时，文件c: est.bmp必须存在-Is the erosion and dilation, thinning algorithm command-line compiler as follows vcvars32 rc bmp.rc cl morph.c bmp.res user32.lib gdi32.lib Note: run-time, the file c: test.bmp must exist

给你提供了学习函数的实例，尽量可以识别图像，有效分类-Give you an instance of the function to learn as much as possible the image can be identified and effective classification

实现图像数据的JPEG-LS标准的压缩，可以实现无损压缩也可以进行有损压缩-Realize image data standard JPEG-LS compression, lossless compression can be lossy compression can also be carried out

程序里包含有一个读取DXF文件的动态库DXF.DLL,代码演示了如何利用该动态库实现对DXF文件夹的读取!-procedures Lane contains a read DXF file of the DXF.DLL. Demonstration of the code on how to use the dynamic for achieving the DXF file folders to read!

这个光盘资料里面包含ARX编程基础和创建编辑基本图形对象的原程序-This CD-ROM which contains ARX programming foundation and basic graphics editor to create the original object program

Graph matching (GM) is a fundamental problem in computer science, and it plays a central role to solve correspondence problems in computer vision. GM problems that incorporate pairwise constraints can be formulated as a quadratic assignment problem (QAP). Although widely used, solving the correspondence problem through GM has two main limitations: (1) the QAP is NP-hard and difficult to approximate; (2) GM algorithms do not incorporate geometric constraints between nodes that are natural in computer vision problems. To address aforementioned problems, this paper proposes factorized graph matching (FGM). FGM factorizes the large pairwise affinity matrix into smaller matrices that encode the local structure of each graph and the pairwise affinity between edges. Four are the benefits that follow from this factorization: (1) There is no need to compute the costly (in space and time) pairwise affinity matrix; (2) The factorization allows the