ImageSegmentation

计算机视觉和视觉测量中常用的椭圆拟合程序。用于视觉测量中的圆形标志点检测。(Computer vision and visual measurement of the ellipse fitting procedure used. Vision for the measurement of circular signs point detection.)

说明：  边缘检测是图像处理和计算机视觉中的基本问题，边缘检测的目的是标识数字图像中亮度变化明显的点。图像属性中的显著变化通常反映了属性的重要事件和变化。这些包括（i）深度上的不连续、（ii）表面方向不连续、（iii）物质属性变化和（iv）场景照明变化。边缘检测是图像处理和计算机视觉中，尤其是特征提取中的一个研究领域。 一阶:?Roberts Cross算子，Prewitt算子，Sobel算子， Kirsch算子，罗盘算子； 二阶： Marr-Hildreth，在梯度方向的二阶导数过零点，Canny算子，Laplacian算子。(Edge detection is a basic problem in image processing and computer vision. Significant changes in image attributes usually reflect significant events and changes in attributes. These include (I) discontinuities in depth, (ii) discontinuities in surface orientation, (iii) changes in material properties, and (iv) changes in scene lighting. Edge detection is a research field in image processing and computer vision, especially in feature extraction.)

OpenCV FaceDetectDirectShow小波图像分割算法(Wavelet image segmentation algorithm)

将图片转化为BMP位图，然后通过逐行扫描识别图片中的数字。(A picture into a BMP bitmap, and then through the progressive scanned image in the figure.)

关于高光谱图像的图像处理技术，RX异常检测技术，代码功能强大，且代码注释很多，对学习很有帮助。(Hyperspectral image on image processing techniques, RX Anomaly Detection technology, powerful code feature, and many code comments, learning helpful.)

说明：  自己编写的图像质量评价函数，包括方差、平均梯度、模糊熵、信息熵(I have written the image quality evaluation function, including the variance, with an average gradient, fuzzy entropy, information entropy)

Ransac拟合直线和最小二乘法拟合的比较，对初次接触ransac的读者帮助很大(Ransac fitting straight line and the least-squares fitting of the comparison, the initial contact with the readers of great help to ransac)

使用高斯消去法的AVO参数反演程序，可以检索模型层数，十分方便实用。(Using the Gauss elimination of the AVO parameter inversion procedure, you can retrieve the model layer, very convenient and practical.)

对图像进行GMM（混合高斯）拟合后用EM算法进行分割(Image GMM (Gaussian Mixture) after fitting algorithm using EM Segmentation)

Matlab版改进的sobel算子边缘检测算法，有效减少边缘断点(Matlab version improved sobel operator edge detection algorithm is effective in reducing edge break)