Computer vision and the machine learning workflow

Computer vision applications with machine learning have a common basic structure. This structure is divided into different steps:

1. Pre-process
2. Segmentation
3. Feature extraction
4. Classification result
5. Post-process

These are common in almost all computer vision applications, while others are omitted. In the following diagram, you can see the different steps that are involved:

Almost all computer vision applications start with a Pre-process applied to the input image, which consists of the removal of light and noise, filtering, blurring, and so on. After applying all pre-processing required to the input image, the second step is Segmentation. In this step, we have to extract the regions of interest in the image and isolate each one as a unique object of interest. For example, in a face detection system, we have to separate the faces...