Computer Vision- Understanding the Machine Perspective

computer vision means the ability of a computing machine to see and interpret the things around or the world as we humans do and possibly much better than that. A human can perform multiple tasks while visualizing and interpreting a scene or a picture. when we talk about computer vision, we aim to provide such a real-time ability to computers.

Basic understanding required to make a computer see and interpret is to understand how the visual information is processed and understood in biological systems? And, What is the nature of computation involved in visualizing and interpretation? It involves a basic understanding of biology, neuroscience, and computer vision.

Example: If someone throws a ball to you, you immediately catch, and it involves a complex process and computation at the neuron level.

  1. Light rays of ball pass through eyes and strikes at the retina.
  2. Retina performs some preliminary processing before sending it through optical nerves to the brain.
  3. Now the visual cortex performs analysis, the brain taps into knowledge base,
  4. Classifies the object and dimensions, and
  5. Predict the reaction by sending signals to the hand to catch the ball.
  6. This takes place in a fraction of a second successfully.

So we can Computer Vision is concerned with the automatic extraction, analysis, and understanding of useful information from a single image or video or a scene. It requires the knowledge of computational algorithms to understand and the processing behind the computer vision or we can say it includes a theoretical and algorithmic basis to achieve automatic understanding.

Computer Vision is an interdisciplinary field that works for high-level understanding from images or videos. It has major two goals:

  1. It aims to come up with computational models of the human visual system.
  2. It also aims to build autonomous systems to perform some of the tasks which the human visual system can perform and even surpass it in many cases.

The need for Computer Vision

  1. Humans have a great role of vision in daily life and schedule.
  2. We live in a 3-D physical world to make the machine understand this 3-D world and also to interact with the 3-D world.
  3. It is important to teach the computer to see and understand the world as humans do.

Related Areas of Computer Vision: Digital Signal Processing, Pattern Recognition, Machine learning, Artificial Intelligence, Deep Learning, and Neural Networks.

Nowadays, computer vision is a rapidly expanding field and advancements in it have made it easier to use for learners to experts. There are some ready to use tools available that are used by the developers.

OpenCV (Open Source Computer Vision Library) is an open-source computer vision and machine learning software library. it is a BSD-licensed library and makes it easy for businesses to utilize and modify the code.OpenCV provides a common infrastructure for computer vision applications and accelerates the use of machine perception in real-world projects.