Image preprocessing is a method used to change or improve digital images before machine learning models take them for analysis. Image preprocessing aims to enhance the quality of the pictures and eliminate noise, distortion, and other parameters that could make the analysis less accurate.
Image Preprocessing Uses
Here are some ways that image preprocessing is used in the AI field:
1. Object Recognition:
Object Recognition: Image preprocessing is used to get the images ready for object recognition models. This might entail resizing, making the colors look the same, and removing the background.
2. Facial Recognition:
Techniques for preprocessing images are used to prepare the pictures for facial recognition models. This can include cropping, rotating, and making the image in a standard format.
3. Medical Imaging:
Medical Imaging: Image preprocessing is essential for medical imaging analysis because it can help eliminate noise and bring out details of specific interest. This could involve removing noise, aligning images, and separating them into parts.
4. Autonomous Vehicles:
Autonomous Vehicles: Image preprocessing is utilized to get images from cameras on autonomous vehicles and make them ready for analysis by machine learning models. It may involve fixing distortions, correcting colors, and separating objects.
