Information about Image Analysis
Image analysis is the extraction of meaningful information from images; mainly from digital images by means of digital image processing techniques. Image analysis tasks can be as simple as reading bar coded tags or as sophisticated as identifying a person from their face.
Computers are indispensable for the analysis of large amounts of data, for tasks that require complex computation, or for the extraction of quantitative information. On the other hand, the human visual cortex is an excellent image analysis apparatus, especially for extracting higher-level information, and for many applications — including medicine, security, and remote sensing — human analysts still cannot be replaced by computers. For this reason, many important image analysis tools such as edge detectors and neural networks are inspired by human visual perception models.
It is the quantitative or qualitative characterization of two-dimensional (2D) or three-dimensional (3D) digital images. 2D images are, for example, to be analyzed in computer vision, and 3D images in medical imaging. The field was established in the 1950s -- 1970s, for example with pioneering contributions by Azriel Rosenfeld, Herbert Freeman, Jack E. Bresenham, or King-Sun Fu.
Each of these application areas has spawned separate subfields of digital image analysis, with a large collection of specialized algorithms and concepts -- and with their own journals, conferences, technical societies, and so on.
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Computers are indispensable for the analysis of large amounts of data, for tasks that require complex computation, or for the extraction of quantitative information. On the other hand, the human visual cortex is an excellent image analysis apparatus, especially for extracting higher-level information, and for many applications — including medicine, security, and remote sensing — human analysts still cannot be replaced by computers. For this reason, many important image analysis tools such as edge detectors and neural networks are inspired by human visual perception models.
Computer image analysis
Computer image analysis largely contains the fields of computer or machine vision, and medical imaging, and makes heavy use of pattern recognition, digital geometry, and signal processing. This field of computer science developed in the 1950s at academic institutions such as the MIT A.I. Lab, originally as a branch of artificial intelligence and robotics.It is the quantitative or qualitative characterization of two-dimensional (2D) or three-dimensional (3D) digital images. 2D images are, for example, to be analyzed in computer vision, and 3D images in medical imaging. The field was established in the 1950s -- 1970s, for example with pioneering contributions by Azriel Rosenfeld, Herbert Freeman, Jack E. Bresenham, or King-Sun Fu.
Digital image analysis
The applications of digital image analysis are continuously expanding through all areas of science and industry, including:- medicine
- microscopy
- remote sensing
- astronomy
- defense
- materials science
- manufacturing
- security
- robotics
- document processing
- assay plate reading
Object-based image analysis
Object-Based Image Analysis (OBIA) is a sub-discipline of geoinformation science devoted to partitioning remote sensing (RS) imagery into meaningful image-objects, and assessing their characteristics through spatial, spectral and temporal scale.Each of these application areas has spawned separate subfields of digital image analysis, with a large collection of specialized algorithms and concepts -- and with their own journals, conferences, technical societies, and so on.
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IMAGE (from Imager for Magnetopause-to-Aurora Global Exploration), or Explorer 78, was a NASA MIDEX mission that studied the global response of the Earth's magnetosphere to changes in the solar wind.
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A digital image is a representation of a two-dimensional image as a finite set of digital values, called picture elements or pixels. The digital image contains a fixed number of rows and columns of pixels.
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Digital image processing is the use of computer algorithms to perform image processing on digital images. Digital image processing has the same advantages over analog image processing as digital signal processing has over analog signal processing — it allows a much wider
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barcode (also bar code) is a machine-readable representation of information (usually dark ink on a light background to create high and low reflectance which is converted to 1s and 0s).
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A facial recognition system is a computer application for automatically identifying or verifying a person from a digital image or a video frame from a video source. One of the ways to do this is by comparing selected facial features from the image and a facial database.
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computer is a machine which manipulates data according to a list of instructions.
Computers take numerous physical forms. The first devices that resemble modern computers date to the mid-20th century (around 1940 - 1941), although the computer concept and various machines
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Computers take numerous physical forms. The first devices that resemble modern computers date to the mid-20th century (around 1940 - 1941), although the computer concept and various machines
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The term visual cortex refers to the primary visual cortex (also known as striate cortex or V1) and extrastriate visual cortical areas such as V2, V3, V4, and V5.
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The goal of edge detection is to mark the points in a digital image at which the luminous intensity changes sharply. Sharp changes in image properties usually reflect important events and changes in properties of the world.
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Traditionally, the term neural network had been used to refer to a network or circuitry of biological neurons. The modern usage of the term often refers to artificial neural networks, which are composed of artificial neurons or nodes.
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In psychology, visual perception is the ability to interpret visible light information reaching the eyes which is then made available for planning and action. The resulting perception is also known as eyesight, sight or vision.
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Computer vision is the science and technology of machines that see.
As a scientific discipline, computer vision is concerned with the theory and technology for building artificial systems that obtain information from images.
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As a scientific discipline, computer vision is concerned with the theory and technology for building artificial systems that obtain information from images.
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Machine vision (MV) is the application of computer vision to industry and manufacturing. Whereas computer vision is mainly focused on machine-based image processing, machine vision most often requires also digital input/output devices and computer networks to control other
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- See also: Radiology, Radiography
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Pattern recognition is a sub-topic of machine learning. It can be defined as
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- "the act of taking in raw data and taking an action based on the category of the data".
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Digital geometry deals with discrete sets (usually discrete point sets) considered to be digitized models or images of objects of the 2D or 3D Euclidean space.
Simply put, digitizing is replacing an object by a discrete set of its points.
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Simply put, digitizing is replacing an object by a discrete set of its points.
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Signal processing is the analysis, interpretation and manipulation of signals. Signals of interest include sound, images, biological signals such as ECG, radar signals, and many others.
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Computer science, or computing science, is the study of the theoretical foundations of information and computation and their implementation and application in computer systems.
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Massachusetts Institute of Technology (MIT) is a private, coeducational research university located in Cambridge, Massachusetts. MIT has five schools and one college, containing 32 academic departments,[3]
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artificial intelligence (or AI) is "the study and design of intelligent agents" where an intelligent agent is a system that perceives its environment and takes actions which maximizes its chances of success.
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Robotics is the science and technology of robots, their design, manufacture, and application.[1] Robotics requires a working knowledge of electronics, mechanics, and software, and is usually accompanied by a large working knowledge of many subjects.
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A quantitative attribute is one that exists in a range of magnitudes, and can therefore be measured. Measurements of any particular quantitative property are expressed as a specific quantity, referred to as a unit, multiplied by a number.
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"Qualitative" is an important qualifier in the following subject titles:and
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- Qualitative marketing research
- Qualitative research
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dimension (Latin, "measured out") is a parameter or measurement required to define the characteristics of an object—i.e., length, width, and height or size and shape.
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Three-dimensional space is the physical universe we live in. The three dimensions are commonly called length, width, and breadth, although any three mutually perpendicular directions can serve as the three dimensions. Pictures are commonly two dimensional, they lack depth.
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A digital image is a representation of a two-dimensional image as a finite set of digital values, called picture elements or pixels. The digital image contains a fixed number of rows and columns of pixels.
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Computer vision is the science and technology of machines that see.
As a scientific discipline, computer vision is concerned with the theory and technology for building artificial systems that obtain information from images.
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As a scientific discipline, computer vision is concerned with the theory and technology for building artificial systems that obtain information from images.
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- See also: Radiology, Radiography
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Azriel Rosenfeld
Born January 19 1931
Died January 22 2004 (aged 73)
Residence U.S.
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Born January 19 1931
Died January 22 2004 (aged 73)
Residence U.S.
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Dr. Herbert Freeman is a computer scientist who made important contributions to the field of automatic label placement, computer graphics, including anti-aliasing, and machine vision.
Dr.
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Jack E. Bresenham is a professor of computer science. He retired from 27 years of service at IBM as a Senior Technical Staff Member in 1987. He taught for 10 years at Winthrop University and has five patents. He has three children: Janet, Linda, and David.
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