This paper presents a novel segmentation algorithm for metallographic images, especially those objects without regular boundaries and homogeneous intensity. In metallographic quantification, the complex microstructures make the conventional approache

用MATLAB实现的基于区域生长算法的图像分割-Implemented using MATLAB-based region growing algorithm for image segmentation

利用遗传算法和基于区域的生长法莱实现图像的分割，突出感兴趣的部分-Using genetic algorithm and region growing method to achieve image segmentation Lay, highlight the interesting part

改进的T- Snake 算法首先在分水岭法中, 对相邻区域以其像素数、灰度均值和灰度方差定义距离, 并据其在图像上建立新的连通图, 以对图像过度分割而产生的一些过小区域合并 其次, 在模型跨边缘时, 利用已分割断层图像中模型内部区域的统计特征, 用区域生长法获取内点并重新参数化模型, 使模型不再跨边缘, 以保证模型形变到正确的边缘-Improved T-Snake algorithm first law in the watershed, the number of pixels in its