hoschek 方法用于曲线拟合 在Hoschekfit 文件中输入数据,拟合曲线段数,拟合误差,最大迭代次数就可以...

《池塘夜降彩色雨》配套源代码- Pond nights rain fall color complementary source code

用于对两幅连续图像进行拼接，模板匹配算法-used for two consecutive image stitching, template matching algorithm

本软件是由作者经过数字图像处理课程的学习，采用vc++.net将其基本算法实现，其算法主要包括： 1.点运算（灰度直方图，直方图均衡处理，线性运算，二值化，灰度化等） 2.几何运算（旋转，放缩，镜像，平移） 3.几何空间增强（均值，中值滤波器，k近邻均值，中值滤波器，Roberts,sobel,priwitt,laplacian,wallis锐化算子等） 4.频率域增强（基2FFT进行空间域到频率域的转换，高斯，理想，巴特沃斯高低通滤波器） 5.形态学（膨胀，腐蚀，开，闭运算，边缘提取） 6.图像复原（加躁）----- 由于时间关系这部分为完成 7.另外加上一个用于读取24位dib的类。-the software is the author of Digital Image Processing courses of study, using vc. Net to its basic algorithm, the algorithm include : 1. Point Operators (histogram, histogram equalization, linear operation, two values, such as Gray) 2. Geometric Operational (rotation, scaling, mirror and translation) 3. geometric space enhancement (mean, median filter, k neighbors Mean, Median Filter, Roberts, segmentation, priwitt, Laplacian, Wallis Sharpening operator, etc.) 4. frequency Domain Enhancement (radix 2 FFT space frequency domain to the domain conversion, Gaussian, ideals, Butterworth High-Low Pass Filter) 5. Morphology (expansion, corrosion, open and close operations, edge extraction) 6. Image

这是一个做美国国旗的程序，可以实现国旗的票动效果-This is a flag of the United States to do procedures, the national flag can be achieved dynamic effects of votes

本程序基本于.Net平台开发，默认支持Access数据库，可扩展为任意数据库，拥有完整的文章发布-jkkjjjjjjjjjjjjjjjjjjjllllllllllllllllllll

一般情况下通用的图片验证码识别，具有自学习过程，很有参考价值-definitive picture verification code identification, self-learning process of great reference value

这个类库可以处理BMP、GIF、PCX、TGA、JPG、TIF格式的图像文件，而且具有图像点处理、图像区域处理的功能，你所要做的只是调用函数而已，不必清楚这些图像文件的内部格式。-the library can handle BMP, GIF, PCX, TGA, JPG, TIF format image files, and images with point processing, image processing functions regional, you have to do it is the function call and not aware of these images document the internal format.

DjVuLibre提供了高效的图像 压缩格式DjVu格式的编码和解码功能。DjVuLibre的使用授权为GPL按照GPL的要求-DjVuLibre provide highly efficient image compression format DjVu-coding and decoding functions. DjVuLibre authorization for the use of the GPL in accordance with the requirements of the GPL

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

摄像机标定-Camera calibration