This section introduces you to some of the most common techniques that can be applied to preprocess images in the context of object segmentation/detection. The preprocess is the first change that we make in a new image before we start with our work and extract the information that we require from it.
Normally, in the preprocessing step, we try to minimize the image noise, light conditions, or image deformations due to the camera lens. These steps minimize the errors when you try to detect objects or segment our image.
If we don't remove the noise, we can detect more objects than we expect because normally noise is represented as a small point in the image and can be segmented as an object. The sensor and scanner circuit normally produce this noise. This variation of brightness or color can be represented in different types, such as Gaussian noise, spike noise, and shot noise. There are different techniques that can be used to remove the noise. We...
