PicTool

说明：  VC++.NET车牌识别、字符分割与归一化处理，图像对象BMP格式，程序将读取车牌的图像信息，归一化图像大小，动态分配存储图片的像素信息的二维数组，找到图像各列，从左列开始,垂直扫描，实施图片局部分割等，有兴趣编写车牌号识别的可参考对比下。(VC ++. NET license plate recognition, character segmentation and normalization processing, image object BMP format, the program will read the license plate image information, normalize the image size, dynamically allocate a two-dimensional array of pixel information to store the picture, and find the image columns , Starting from the left column, vertical scanning, partial image segmentation, etc. If you are interested in writing the license plate number recognition, please refer to the comparison.)

我自己做的一个bmp文件进行24位真彩转256灰度和二进制的程序，并能用sobel算法，识别物体的边界。 (I myself make a bmp file for 24-bit true color to 256 gray-scale and binary procedures and sobel algorithm can be used to identify object boundaries.)

基于otsu的自适应阀值canny边缘检测(adaptive canny edge detection based on otsu)

26个不同影像处理程序,以VC++开发,是了解影像入门好帮手(26 different image processing procedures to VC++ Development is helpful to understand the image entry)

说明：  遥感图像.img图像与raw格式图像的之间的转换(remote sensing images. Img images with the raw image format conversion between the)

针对大尺度图像配准和不同传感器图像配准问题, 介绍了一种基于 SIFT 的图像配准方 法。(For large-scale image registration and image registration problem from different sensors, introduces a SIFT-based image registration method.)

此程序实现二十四位BMP到八位BMP图像的转换(this program to 24 BMP eight BMP image conversion)

Complete class-based image processing, contains all of the source code, auto image, There are cycle detection, periodic testing, MIT Artificial Intelligence Laboratory identification of the target source.

1.RAW格式转换为BMP格式 2.灰度线性拉伸 3.局部处理 4.几何处理 5.二值化 6.模板匹配 7.影像融合(1.RAW format converted to BMP format 2. grayscale linear stretch 3. local processing 4. geometric processing 5. binaryzation 6. template matching 7. image fusion)

第8章 图象的检测及模板匹配 图象的分割与检测(识别)实际上是一项非常困难的工作。很难说清楚为什么图象应该分割成这样而不是那样。(Chapter 8 Detection of image template matching and image segmentation and detection (recognition) is actually a very difficult task. It is hard to say clearly why the image should be divided into such and not as.)