Image segmentation is a commonly used technique in digital image processing and analysis to partition an image into multiple parts or regions, often based on the characteristics of the pixels in the image. Image segmentation could involve separating foreground from background, or clustering regions of pixels based on similarities in color or shape. For example, a common application of image segmentation in medical imaging is to detect and label pixels in an image or voxels of a 3D volume that represent atumor in a patient’s brain或其他器官。
多年来,多年来,使用域特定知识在多年上已经开发了几种算法和图像分割技术,以有效解决特定应用区域中的分割问题。这些应用包括医学成像,自动化驾驶,视频监控和机器视觉。
在癌症的医学诊断过程中,病理学家用苏木精和曙红(H&E)染色身体组织,以区分组织类型。然后他们使用调用的图像分割技术聚类识别图像中的那些组织类型。聚类is a method to separate groups of objects in a scene. The K-means clustering algorithm finds separations such that objects within each cluster are as close to each other as possible, and as far from other objects in other clusters as possible.
在为自动驾驶汽车等自动车辆的观念设计时,语义细分通常被用来帮助系统识别和locate vehicles and other objects on the road.
图像分割涉及将图像转换成由掩模或标记图像表示的像素区域的集合。通过将图像划分为片段,您只能处理图像的重要段而不是处理整个图像。
一种常见的技术是在像素值中寻找突然的不连续性,其通常表示定义区域的边缘。
Another common approach is to detect similarities in the regions of an image. Some techniques that follow this approach are region growing, clustering, and thresholding.
多年来,多年来使用域特定知识在多年上已经开发了各种其他执行图像分割的方法,以有效地解决特定应用领域的分割问题。
借MATLAB®那you can:
使用交互式图像分段器应用程序,您可以迭代地尝试在实现所需结果之前逐次段的方法。例如,您可以使用该应用程序segment and further refinethe results of an MRI image of a knee with different methods.
This Color Thresholder app lets you apply thresholding to color images by manipulating the color of the images interactively, based on different color spaces. For example, you can use the Color Thresholder app to创建二进制掩码使用点云控件进行彩色图像。
借functions in MATLAB andImage Processing Toolbox™,您可以在不同的图像分割技术上进行实验和构建专业知识,包括阈值处理,聚类,基于图形的分割和区域生长。
使用Otsu’s method,imbinarize
在2D或3D灰度图像上执行阈值处理以创建二进制图像。从RGB彩色图像生成二进制图像,使用RGB2GRAY.
to first convert it to a grayscale image.
This technique lets you create a segmented labeled image using a specific clustering algorithm. Using K-means clustering–based segmentation,Imsegkmeans.
segments an image into K number of clusters.
基于图形的分段技术,如懒惰捕捉使您可以将图像分段为前景和背景区域。Matlab允许您以编程方式在图像上执行此分段(leazysnapping.
) or interactively using the Image Segmenter app.
地区生长是一种基于简单的区域(也被分类为基于像素的)图像分割方法。一种普遍使用的算法是ActiveCont.
那which examines neighboring pixels of initial seed points and determines iteratively whether the pixel neighbors should be added to the region. You can also perform this segmentation on images using the Image Segmenter app.
使用convolutional neural networks (CNNs), a deep learning technique called semantic segmentation lets you associate every pixel of an image with a class label. Applications for semantic segmentation include autonomous driving, industrial inspection, medical imaging, and satellite image analysis.
使用MATLAB,您可以使用图像的集合及其相应的标记图像设计和培训语义分段网络,然后使用训练网络标记新图像。至label the training images那you can use the Image Labeler, Video Labeler, or Ground Truth Labeler apps.