Computer vision is a sub-field of study that focuses on the problem of helping computers to see. As you can see in the explanation above, this is a multidisciplinary field that can broadly be referred to as a subfield of artificial intelligence and machine learning, which may involve using specialized methods and making use of computer vision algorithms in general. As a multidisciplinary field of study, indirectly they can be said to be quite messy, especially with techniques borrowed and reused from different fields of engineering and computer science.

One particular problem in his vision can be easily overcome by man-made statistical methods, whereas another may require large and complex ensembles of common machine learning algorithms. It is important to know the purpose and function of computer vision. After we know what computer vision is, then of course we also have to know about the purpose and function of computer vision in particular. Well, as explained by experts and experts in the book entitled “Computer Vision: A Modern Approach (2002)” computer vision as a field is an intellectual limit.

Like any restriction, computer vision is attractive and disorganized, and there is often no reliable authority to appeal to it. The main purpose of computer vision, of course, is to understand the content of digital images. Usually, this involves developing methods that attempt to reproduce our human-like visual abilities. Then, related to its main function, computer vision serves to understand the content of digital images which may involve extracting descriptions from images, which may be objects, text descriptions, three-dimensional (3D) models, and so on.

We can conclude that Computer Vision (CV) or computer vision is a computer way of training a digital system to process, analyze, and understand the visual world. The end goal is not only to have computer vision algorithms “know” what each object is, but also to react to what they “see”.