Computer Vision is a field of Machine Learning that enables computers and automative systems to derive meaningful information from digital images, videos and other visual inputs. With other spheres of AI work to make the computers to think, Computer Vision is serves as one of the biggest components that gives them the information to do so.
- Image Classification: the task of assigning an input image one label from a fixed set of categories.
- Object Localization: the task of assign a single label to an image corresponding to the “main” object.
- Object Detection: the task of making bounding boxes around real life objects in an image or video.
- Image Segmentation: the task of partitioning a digital image into multiple segments (sets of pixels, also known as image objects).
The purpose of segmentation is to make an image more intelligible and easier to examine by simplifying and/or changing its representation. In humans to objects and boundaries (lines, curves, etc.) in images are often located via an unconscious image segmentation.
In Layman's terms, image segmentation is the process of assigning a label to every pixel in an image such that pixels with the same label share certain characteristics.
- Thresholding Segmentation
- Edge-Based Segmentation
- Region-Based Segmentation
- Watershed Segmentation
- Clustering-Based Segmentation Algorithms
- Neural Netw)orks for Segmentation
