glint

说明：  简单的数字图像处理程序，实现灰度化，二值化，边缘检测等(Simple digital image processing program, graying, binarization, edge detection, etc....)

毕业设计，基于内容的图像检索，支持的检索特征包括 sift,颜色直方图，灰度矩阵，HU不变矩，边缘方向直方图，检索方法使用K-means和K-D树两种，需要OPENCV支持，运行时请先选定一个文件夹来生成特征库，特征库用access数据库保存，只支持JPG文件(Graduate design, content-based image retrieval, search features, including support sift, color histogram, gray matrix, HU moment invariants, edge direction histogram, retrieval method using the K-means and KD trees are two kinds of needs OPENCV support Please select a runtime folder to generate the feature library, feature library with access database save, only supports JPG files)

说明：  SIFT算法的区域匹配，比原有的SIFT+KD树匹配更加高效、准确。(different area SIFT algorithm which is better than the original SIFT and KD tree match.)

说明：  图像检索的的基于语义的图像检索 纹理图像检索 图像的特征提取方法(Image Retrieval of semantic-based image retrieval image retrieval image texture feature extraction methods)

图像去雾c++版源代码，实现效果还不错，可直接运行。(Fog to remove the c++ version of the source code, the effect is not bad, can be run directly.)

读取图像，将RGB图像转化为灰度图像，显示并保存(The RGB image is transformed into gray image)

本程序使用dcmtk库，可以显示大部分的DICOM图像。非压缩、压缩黑白图像以766灰阶显示，彩色图像正常显示。 对于初用dcmtk库的开发者来说，入门较难，本程序已使用VC6工程将主要库加入工程中，可以参考本工程的设置。另外，对于高于8位的黑白图像，本程序也提供一个处理方法的参考。(This procedure used dcmtk library, you can see that the majority of the DICOM image. Non-compressed, compressed to 766 gray-scale black-and-white images show that color image display. Dcmtk library used for the early developers, the entry more difficult, the procedure has been in use for the main library VC6 project will join the project, can refer to the project settings. In addition, higher than the 8-bit black-and-white images, the program also provides a reference method.)

用大整数乘法来计算两个n位二进制数相乘(With large integer multiplication to calculate the multiplication of two n-bit binary number)

C语言编程，利用矢量量化思想进行图像有损压缩和解压缩(C language programming, using vector quantization thoughts lossy image compression and decompression)

用来进行多目标跟踪的JPDA算法的的MATLAB程序包. 跟踪效果还行. (Used for multi-target tracking JPDA algorithm of the MATLAB package tracking performance is okay.)