Computer vision applications with machine learning have a common basic structure. This structure is divided into different steps:
- Pre-process
- Segmentation
- Feature extraction
- Classification result
- 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...
