pain_gain0的博客

1. 流程示意图1.1 将 所有大于0 的像素值，标记为11.2 计算连通分量，移除CT床架import matplotlib.pyplot as pltfrom PIL import Imageimport numpy as npimg = Image.open("/Applications/Research/Experiments/SynSegExperiment/Model_Results/Plot/unet_feature_visualize/00051.png")#

TextonBoost: Joint Appearance, Shape and Context Modeling for Multi-class Object Recognition and SegmentationIndoor Scene Segmentation using a Structured Light Sensor

参考文献：https://zh.wikipedia.org/wiki/索貝爾算子代码：# reference : https://zh.wikipedia.org/wiki/索貝爾算子from skimage import filters,ioimport numpy as npimport matplotlib.pyplot as pltgx = np.array([[-1,0,1],[-2,0,2],[-1,0,1]])gy = np.array([[1,2,1],[0,0,0

膨胀：是使图像中的目标“生长”或“变粗”的操作。这个特殊的方法和变粗程度由被称为结构元的形状来控制【1】。对断开的字符文本的二值图像进行膨胀操作。图像来源：https://www.google.com.hk/url?sa=i&url=https%3A%2F%2Fdocplayer.net%2F49492134-Morphological-image-processing....