资源列表
Samples-Environments-for-Microsoft-Chart-Controls
- The samples environments for Microsoft Chart Controls for .NET Framework 4 contain over 200 samples for both ASP.NET and Windows Forms, covering every major feature in Chart Controls for .NET Framework 4. See every major feature in action and learn a
CAD-Drawing
- Its an Autocad drawing for flying Toy Pipes.
CircleFind
- 打开图片，转化为灰度图，利用圆周差分法在图像上搜索圆-Open the picture, converted to grayscale, use the circumferential difference method in image search circle
ObjectArxswgl
- 本实例为VS2005编写的ARX事务管理实例，特别是AcTransaction::getObject()和close()的使用方法，作了正确演示。-ARX transaction management example this example is written in VS2005, especially in AcTransaction:: getObject () and close () method of use, make the correct demonstration.
MATLAB-digital-image-processing-
- 《数字图像处理及MATLAB实现》杨杰 MATLAB 环境下的图像变换、图像增强、图像复原、图像压缩、小波变换等等完整源代码-The digital image processing and MATLAB Yang jie MATLAB environment image transformation, image enhancement, image restoration, image compression, wavelet transform, and so on comple
1
- 在MATLAB平台上通过实验进一步了解离散小波变换，加深对小波变换的理解-Digital watermarking based on Wavelet Transform
DWT
- 基于小波变换的数字水印,通过编码进一步理解小波变换-Digital watermarking based on Wavelet Transform
OpenCV-feature-extraction
- openCV特征提取代码总结，包括：颜色直方图提取，形状特征提取，角点提取、Hough直线提取、边缘提取、纹理特征提取等等。-OpenCV feature extraction code summary, including: color histogram extraction, shape feature extraction, angular point extraction, Hough straight line extraction, edge detection and textu
QX_He
- solidworks 做的零件，solidworks初学者可以用作学习的参考。-solidworks do parts, solidworks beginners learning can be used as a reference.
PGA
- 相位梯度自聚焦算法（PGA）的matlab程序实现，合成孔径雷达中最经典最常用的自聚焦和运动误差补偿方法-The phase gradient autofocus algorithm (PGA) of matlab implementation, the most classic of the most commonly used in synthetic aperture radar self-focusing and the motion error compensation method
LBF
- 主要讲述了主动轮廓法，其中一种经典方法。-Focuses on the active contour method, one of the classic methods.
chepaishibie
- 该程序涉及到自动提取车牌图像、自动分割字符，进而对分割字符的图像进行图像识别。-The program involves the automatic extraction of the license plate image, automatic segmentation of characters, and then dividing the character image on image recognition.