基于区域融合的半监督的图像分割算法。首先在背景和前景手动设置初始分割标记，在迭代过程中不断通过区域融合操作获得最大相似度的区域，从而实现目标分割。-Regional integration based on semi-supervised image segmentation. First of all, in the background and foreground segmentation manually set the initial marking, in the iteration

数字图像处理和监督分类基本操作。包括点运算、几何变换、图像增强、频域滤波、彩色图像处理，形态学变换、图像分割、特征提取、识别初步等。- The basic operation of digital image processing and supervised classification. Including point arithmetic, geometric transformation, image enhancement, frequency domain filtering, co

CVPR2012_oral Weakly Supervised Structured Output Learning for Semantic Segmentation-We address the problem of weakly supervised semantic segmentation. The training images are labeled only by the classes they contain, not by their location in t

基于改进的马尔可夫、监督分类方法实现的图像分割、效果较好。-Improved Markov-based supervised classification methods to achieve image segmentation, better results.