Introduction to Machine Vision

Introduction to Machine Vision

Machine vision is the ability of a computer to "see". The concept of seeing involves a number of different tasks such as recognition of objects, tracking of objects, interpretation of scenes and objects and detection of new activities. Machine vision is also used for automatic recovery of 3-dimensional models of the environment. Machine vision is the technology and methods that are used to provide the imaging-based automatic inspection and analysis for such applications as automatic inspection, process control, and robot guidance in industry. The scope of machine vision is broad.

Machine vision is considered to be sub-field of artificial intelligence. AI studies the computational aspects of intelligence. There are two important specifications in any vision system and they are the sensitivity and the resolution. The sensitivity is simply understood as the ability of a machine to see in dim light or to detect the weak impulses at invisible wavelengths. The resolution is referred as the extent to which a machine can differentiate between the objects. In general, the better the resolution, the more confined the field of vision. Sensitivity and resolution are interdependent. All other factors held the constant such as increasing the sensitivity reduces the resolution and improving the resolution reduces the sensitivity.

The applications of the machine vision system are presented below:

• Robotics:Machine vision can make a robot manipulator much more versatile by allowing it to deal with variations in parts, position, and orientation.
• Medicine: It assists a physician to reach a diagnosis. It does this by constructing 2D or 3D anatomy models of the human body. It analyzes the image to extract useful features.
• Remote Sensing: It senses the remote by taking the images from high altitudes such as from air-crafts or satellites. It analyses the image by generating a description.
• Cartography
• Meteorology
• Quality inspection
• Reconnaissance.

There is no universal machine vision system as there is only one system for each application.

Machine vision hardware

The machine vision hardware is the personal computers, workstations etc. The 2D image arrays of gray level or the color values are used for the signals. The modules are generally low-level processing, shape from texture, motion, contours etc. The machine vision hardware consists of simple interconnections. There exist no parallelism.

References:

1. Elaine Rich, Kevin Knight 1991, "Artificial Intelligence".
2. Nilsson, Nils J. Principles of Artificial Intelligence, Narosa Publishing House New Delhi, 1998.
3. Norvig, Peter & Russel, Stuart Artificial Intelligence: A modern Approach, Prentice Hall, NJ, 1995
4. Patterson, Dan W. Introduction to Artificial Intelligence and Expert Systems, Prentice Hall of India Private Limited New Delhi, 1998.