11-05-2012, 01:01 PM
Theory of Image Analysis : Applications and Implications in the present Global Technical Scenario
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Abstract
Image analysis is the extraction of meaningful information from images. Image analysis tasks can be as simple as reading bar coded tags or as sophisticated as identifying a person from their face.
In 1963, the first Image Analysis system to use a television camera as the input device was developed. This system was made by Metals Research Ltd., Cambridge, England, and was called the Quantimet A. The widespread use of the personal computer led to further advances in Image Analysis technology in the early 1980's. After that the manufacturers of image analysis systems create user interfaces so that relatively simple instructions can be used to interface with the software libraries and thus control the image processing functions. The high speed of the hardware boards allow complex image analysis operations to be performed with simple instructions.
In these days Image analysis covers a wide territory from astronomy to microbiology. Today's fourth generation Image Analysis systems represent a new marriage of hardware and software. In the 48 years since the Quantimet A was introduced, image analyzers have grown and evolved into very powerful, very useful tools for the micro structural analyst.
This paper discusses some theory about Image Analysis and the present applications of this in many fields.
Key words: Astronomy, Microbiology, Micro structural.
Introduction
o Image analysis is the extraction of meaningful information from images. It is the quantitative or qualitative characterization of two-dimensional (2d) or three-dimensional (3d) digital images.
o Image analysis tasks can be as simple as reading bar coded tags or as sophisticated as identifying a person from their face.
Historical Back Ground
o In 1963, the first analysis system to use a television camera as the input device was developed. This system was made by Metals Research Ltd., Cambridge, England, and was called the Quantimet A . The term 'QTM' has been applied to image analysis systems because the Quantimet A was referred to as a Quantitative Television Microscope. This was the beginning to the age of automation.
o The successor to this system was the Quantimet B. This was the first commercially successful system. It was capable of making simple stereological measurements of an entire field of view as well as offering a digital readout of the gray level. This system was introduced in 1968. In conjunction with a light pen, measurements of properties of individual objects, were possible for the first time. A fully digital Image Analysis system, the Quantimet 720, was introduced by IMANCO (Metal Research) in 1969.
o Major advances in texture analysis and mathematical morphological analysis were being developed at Ecole de Mines in Paris, France .This group was responsible for developing image erosion, dilation, skeletonization and other concepts, plus the use of Boolean binary logic. The first Image Analysis system to utilize these functions was the Leitz TAS, Texture Analysis System introduced in 1974. Buehler's original image analyzer, the OMNlMET was introduced in 1978. As computer systems became faster, software based Image Analysis systems were introduced by Joyce-Loebl, KONTRON and Cambridge Instruments. Complete images could be stored in the computer memory of these systems; thus, gray and binary image processing was possible. The widespread use of the personal computer led to further advances in Image Analysis technology in the early 1980's.
Need of the Study
o Today's automated image analysis system has been at the peak of developments for over a century. Image analysis has grown and evolved extraordinarily. No field remains unturned as far as immune from Image Analysis is concerned. It also forms a core area of research within the computer science and engineering disciplines at most of the top universities and institutes in the developed countries. As such, it forms the basis for all kinds of future visual automation. The fourth generation Image Analysis systems represent a new combination of hardware and software. There are many different techniques used in automatically analysing images. Each technique may be useful for a small or wide ranges of tasks. Special processing boards that fit in standard microcomputers are used to perform functions such as gray level transformations and numerous binary operations. These boards are composed of numerous modules, and the software modules are used to control the hardware modules. The software libraries use programming languages like C, C++, and Java. The manufacturers of image analysis systems create user interfaces so that relatively simple instructions can be used to interface with the software libraries and thus control the image processing functions . Use of user friendly interfaces leads to high speed of the hardware boards allowing complex image analysis operations to be performed with simple instructions.
Applications
In these days Image analysis system covers wide territory from astronomy to microbiology. A computer or electrical device automatically studies an image to obtain useful information from it. That device is often a computer but may also be an electrical circuit, a digital camera or a mobile phone. The applications of digital image analysis are continuously expanding through all areas of science and industry, including:
o Medicine:
A CT scan image showing a ruptured abdominal aortic aneurysm
Medical imaging is the technique and process used to create images of the human body for clinical purposes like diagnosing and examining the disease which includes the study of normal anatomy and physiology. Imaging of removed organs and tissues can be performed for medical reasons. Such procedures are not usually referred to as medical imaging, but rather are a part of pathology.
o Microscopy:
Malarial parasite revealed through
the use of fluorescence microscopy.
Microscope image processing is a broad term that covers the use of digital image processing techniques to process, analyze and present images obtained from a microscope. Such processing is now commonplace in a number of diverse fields such as medicine, biological research, cancer research, drug testing, metallurgy, etc. A number of manufacturers of microscopes now specifically design in features that allow the microscopes to interface to an image processing system.
o Remote sensing:
Ramasetu1_NASA.jpg
Remote sensing is the acquisition of information about an object or phenomenon, without making physical contact with the object. In modern usage, the term generally refers to the use of aerial sensor technologies to detect and classify objects in the atmosphere, on the Earth’s surface, and in the oceans from aircrafts or satellites.
o Astronomy:
Astronomy picture of the day
May 25, 2009
Astrophotography is a specialized type of photography that entails recording images of astronomical objects and large areas of the night sky. Besides being able to record the details of extended objects such as the Moon, Sun, and planets, astrophotography has the ability to image objects invisible to the human eye such as dim stars, nebulae, and galaxies.
o Materials Science:
Image of Nanofibre
Materials science is an interdisciplinary field applying the properties of matter to various areas of science and engineering. This scientific field investigates the relationship between the structure of materials at atomic or molecular scales and their macroscopic properties. It is also an important part of forensic engineering and failure analysis. Materials science also deals with fundamental properties and characteristics of materials.
o Machine vision:
Image of a sewing machine
Machine vision usually refers to a process of combining automated image analysis with other methods and technologies to provide automated inspection and robot guidance in industrial applications. As a scientific discipline, computer vision is concerned with the theory behind artificial systems that extract information from images. The image data can take many forms, such as video sequences, views from multiple cameras.
o Security:
Biometric palm image
Image and video processing play an important role in the development of technologies for dealing with security issues. Surveillance cameras are widely diffused as means of crime reduction. Image analysis tools are used in the forensics fields like biometric analysis, photo and video recordings authentication, image enhancement etc.
o Robotics:
A robot that identify weeds
Robotics is the branch of technology that deals with the design, construction, operation, structural disposition, manufacture and application of robots. Robotics is related to the sciences of electronics, engineering, mechanics, and software. RoboRealm is an application for use in computer vision, image analysis, and robotic vision systems.