Analysing and manipulating the image to get a desired image (segmented image in our case) and.Importing the image via image acquisition tools.Image processing mainly include the following steps: Image segmentation is one of the phase/sub-category of DIP. Gonzalez, Digital Image Processing means processing a digital image by means of a digital computer in order to get enhanced image either to extract some useful information. Referring to one of the most famous book Digital Image Processing by Rafael c. Advantages and disadvantages of using DIP image segmentation methods.What are the latest and efficient DIP methods used for image segmentation.A brief introduction to different image segmentation methods using DIP.What is digital image processing and its components?.So let’s start and jump in to the ocean of knowledge. The following blogs will contain the machine learning and deep learning methods for potential image segmentation.
This is the part 1 of a 3 parts blogs where I will discuss different digital image processing methods which can be helpful in achieving our goal of image segmentation. This is called image segmentation where we segment/divide an image or extract different kinds of objects in it. Now the question is how can we make a computer to do this thinking or how can we design an algorithm such that it captures all the differentiating methods for each fruit and gives us an output as shown in figure 1 (right). that acts as a factor of differentiation between them. This can be done by analysing fruits that have different colours, shapes, texture, etc.
If we analyse our thinking or visual processing that might have took place in our brain, we can answer the question by listing various methods of differentiating bananas with apples and oranges, oranges with apples and bananas, etc. Left: Original Image of a fruit basket Right: Segmented image of a fruit basket
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