The Computer Vision Workshop by Hafsa Asad Vishwesh Ravi Shrimali and Nikhil Singh
Author:Hafsa Asad, Vishwesh Ravi Shrimali, and Nikhil Singh
Language: eng
Format: epub
Publisher: Packt Publishing Pvt. Ltd.
Published: 2020-07-24T00:00:00+00:00
GrabCut Technique
Before we go into the details of this amazing technique, we need to understand the term Image Segmentation, which will form the very basis of GrabCut. In layman's terms, an image segmentation task comprises dividing the pixels into different categories based on the class they belong to. Here, the classes we are looking for are just the background and foreground. This means that we want to segment the image by deciding what region of the image is part of the background and what region of the image is part of the foreground.
Note
In deep learning, image segmentation is a very big topic and is comprised of segmenting an image based on its classes, sometimes based on semantics, and so on. For now, we can consider GrabCut a simple background removal technique, though technically it can also be considered as an image segmentation technique with only two primary classes in mind – background and foreground. It's also important to note here that GrabCut uses not two, but four labels that we will discuss later in this section. But the basic idea will stay the same – remove the background from the image.
For example, consider the following image:
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