How human eye sees things?
It’s a pretty natural phenomenon for us, but making machines see the way we see is more difficult than we think.
Computer vision history started as a summer project related to AI and has turned into a fully established field of science within the last five decades. It is hard to say what lies in the cards for this science.
What is Computer Vision?
Computer vision is a scientific field that deals with how computers can be made to gain high-level understanding from photos or videos. From the perspective of engineering, it seeks to automate tasks that the human visual systems can do.
How does a Computer ‘See’ an Object?
After analyzing the phrase ‘computer vision and image understanding’, it will be understandably clear what it means, namely, “How does a computer see?”
To understand how a computer sees, we need to figure out what it can see.
It extracts, analyze and understand the useful information from a single image or sequence of images. It involves the development of a theoretical and algorithmic basis to achieve automatic visual understanding.
Computer vision works by analyzing the different components of the image. A simple example can be finding the edges in an image. We need to apply a kernel to replicate the differentiation function in the brightness values in the pixels, and then set a threshold where the derivative is high - EDGES
Computer Vision and Image Understanding – The Basics:
In order to make your computer intelligent enough that it can recognize your dog in a photo, you need you master several skills.
In order to fully understand computer vision you need to know about image processing fundamentals, artificial intelligence, pattern recognition, bit of mathematics, physics and signal processing.
In practice, you don’t necessarily have to know all of them but at least have a basic understanding of these if you want to fully understand computer vision.
There are many applications of Computer Vision in Artificial Intelligence operating in the world. Some of them are:
1. Manufacturing Application; an automatic inspection based on images
2. Species Identification System; to identify object & species using their properties
3. Industrial Robot; Controlling processes like monitoring robots. Robots used in car manufacturing industries.
4. Visual surveillance; counting/identifying people, detecting events, target recognition.
5. medical image analysis; Modeling objects or environments (using drones can give analysis about climatic factors that leads to change in vegetation)
6. Mobile robot; Navigation
7. Indexing databases of images and image sequences; Organizing information
How to explore more?
This is a very vast field, at a point we think, we have overloaded ourselves with so much information. But, there is a lot of stuff to explore.
One good approach should be to have a look at some of the graduate seminar courses to get an idea of current research directions in Computer Vision through rich academic papers.