computer vision

What is computer vision?

Computer vision is an area of computer science that enables computers to see, identify and process images as human vision does, and then provide an appropriate output. It is like communicating human intelligence to a computer.

Computer vision is linked with artificial intelligence, as the computer must show what it sees, and then perform the analysis.

Computer vision sees, processes, and provides useful results based on observations. For example, a computer creates a 3D image from a 2D image, such as in cars, and provides important data to the car driver.

In this way, human vision has completed a complex task, for identifying the object, processing data, and deciding what to do. Computer vision enables computers to perform tasks as humans can do with the same efficiency.

It includes methods for getting, processing, analyzing, and understanding digital images, and getting high dimensional data from the real world in order to produce numerical or symbolic information. The transformation of visual images into descriptions of the world processes and do the appropriate action. The image is the symbolic information using models constructed through geometry, physics, statistics, and learning theory.

It is the theory behind artificial systems that get information from images. The data can be taken in different ways, such as video sequences, views from multiple cameras, multidimensional data from a 3D scanner, and medical scanning devices. CV applies its theories and models to the building of cv systems through technological ways.

Subdomains of computer vision include the following;

  • scene reconstruction
  •  Object detection
  • Event detection
  •  Video tracking
  • Object recognition
  •  3D pose estimation
  •  Learning
  • Indexing
  • Motion estimation
  •  Visual servoing
  •  3D scene modeling
  •  Image restoration

International journal of computer vision

The International Journal of Computer Vision (IJCV) was published by Springer in 1987. The current co-editors in chief are M. Hebert; S. Lazebnik; X. Tang.

It is helpful for academicians, researchers, and practitioners regarding the latest developments in the areas of science and technology of machines, imaging, and their related applications, systems, and tools. It contains unique articles, innovative research in computer science, education, security, government, engineering disciplines, software industry, vehicle industry, medical industry, and other fields.

It also has book reviews, position papers, editorials by leading scientific figures, as well as additional online material, such as still images, video sequences, data sets, and software.

It is necessary for the science and engineering of this fast-growing field.

Computer vision applications

Following are the few vision applications;

  • Cancer Detection
  • Cell Classification
  • Movement Analysis
  • Mask Detection
  • Tumor Detection
  • Disease Progression Score
  • Healthcare and rehabilitation
  • Medical Skill Training

Computer vision and image processing

Computer Vision

Computer vision comes from image processing by using the techniques of machine learning. It applies machine learning to recognize patterns for the interpretation of images. It can distinguish between objects, classify them and sort them according to their size. It takes images as an input and gives output in the form of information on size and color intensity etc.

Following are the components of a machine vision system;

  • Camera
  • Lighting devices
  • Lens
  • Frame grabber
  • Image processing software

Image Processing

Digital image processing was made at NASA’s Jet propulsion laboratory in the 1960s, to convert the signals from the ranger spacecraft to digital images with the use of computers. Digital imaging has a wide range of applications in medicine. Its uses include Computed Aided Tomography (CAT) scanning and ultrasounds.

Image processing is the application of mathematical functions and transformations of images being done over the image itself. It is a two-dimensional signal, which is made of rows and columns of pixels. Magnetic Resonance Imaging (MRI), records the excitation of ions and transforms it into a visual image.

For one-dimensional signals, images also can be filtered with various low pass filters (LPF) and high pass filters (HPF).