Image analysis: Difference between revisions

Source: Wikipedia, the free encyclopedia.
Browse history interactively
← Previous editNext edit →
Content deleted Content added
VisualWikitext
Alphabatize list
Correction to Alphabetize
Line 22: Line 22:
==Digital Image Analysis==
==Digital Image Analysis==
Digital Image Analysis is when a computer or electrical device automatically studies an image to obtain useful information from it. Note that the 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:
Digital Image Analysis is when a computer or electrical device automatically studies an image to obtain useful information from it. Note that the 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:
⚫
*[[plate reader|assay micro plate reading]], such as detecting where a chemical was manufactured.
*[[astronomical image processing|astronomy]], such as calculating the size of a planet.
*[[astronomical image processing|astronomy]], such as calculating the size of a planet.
*[[defense (military)|defense]]
*[[defense (military)|defense]]
Line 31: Line 32:
*[[microscope image processing|microscopy]], such as counting the germs in a swab.
*[[microscope image processing|microscopy]], such as counting the germs in a swab.
*[[optical character recognition]], such as automatic license plate detection.
*[[optical character recognition]], such as automatic license plate detection.
⚫
*[[plate reader|assay micro plate reading]], such as detecting where a chemical was manufactured.
*[[remote sensing]], such as detecting intruders in a house, and producing land cover/land use maps.<ref>{{cite journal|last1=Xie|first1=Y.|last2=Sha|first2=Z.|last3=Yu|first3=M.|title=Remote sensing imagery in vegetation mapping: a review|journal=Journal of plant ecology|date=2008|volume=1|issue=1|pages=9–23|doi=10.1093/jpe/rtm005}}</ref><ref>{{cite journal|last1=Wilschut|first1=L.I.|last2=Addink|first2=E.A.|last3=Heesterbeek|first3=J.A.P.|last4=Dubyanskiy|first4=V.M.|last5=Davis|first5=S.A.|last6=Laudisoit|first6=A.|last7=Begon|first7=M.|last8=Burdelov|first8=L.A.|last9=Atshabar|first9=B.B.|last10=de Jong|first10=S.M|title=Mapping the distribution of the main host for plague in a complex landscape in Kazakhstan: An object-based approach using SPOT-5 XS, Landsat 7 ETM+, SRTM and multiple Random Forests|journal=International Journal of Applied Earth Observation and Geoinformation|date=2013|volume=23|pages=81–94|doi=10.1016/j.jag.2012.11.007}}</ref>
*[[remote sensing]], such as detecting intruders in a house, and producing land cover/land use maps.<ref>{{cite journal|last1=Xie|first1=Y.|last2=Sha|first2=Z.|last3=Yu|first3=M.|title=Remote sensing imagery in vegetation mapping: a review|journal=Journal of plant ecology|date=2008|volume=1|issue=1|pages=9–23|doi=10.1093/jpe/rtm005}}</ref><ref>{{cite journal|last1=Wilschut|first1=L.I.|last2=Addink|first2=E.A.|last3=Heesterbeek|first3=J.A.P.|last4=Dubyanskiy|first4=V.M.|last5=Davis|first5=S.A.|last6=Laudisoit|first6=A.|last7=Begon|first7=M.|last8=Burdelov|first8=L.A.|last9=Atshabar|first9=B.B.|last10=de Jong|first10=S.M|title=Mapping the distribution of the main host for plague in a complex landscape in Kazakhstan: An object-based approach using SPOT-5 XS, Landsat 7 ETM+, SRTM and multiple Random Forests|journal=International Journal of Applied Earth Observation and Geoinformation|date=2013|volume=23|pages=81–94|doi=10.1016/j.jag.2012.11.007}}</ref>
*[[robotics]], such as to avoid steering into an obstacle.
*[[robotics]], such as to avoid steering into an obstacle.

Revision as of 15:26, 20 June 2016

Image analysis is the extraction of meaningful information from images; mainly from digital images by means of digital image processing techniques.[1] Image analysis tasks can be as simple as reading bar coded tags or as sophisticated as identifying a person from their face.

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

Jack E. Bresenham, or King-Sun Fu
.

Techniques

There are many different techniques used in automatically analysing images. Each technique may be useful for a small range of tasks, however there still aren't any known methods of image analysis that are generic enough for wide ranges of tasks, compared to the abilities of a human's image analysing capabilities. Examples of image analysis techniques in different fields include:

Digital Image Analysis

Digital Image Analysis is when a computer or electrical device automatically studies an image to obtain useful information from it. Note that the 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:

  • assay micro plate reading, such as detecting where a chemical was manufactured.
  • astronomy
    , such as calculating the size of a planet.
  • defense
  • filtering
  • machine vision, such as to automatically count items in a factory conveyor belt.
  • materials science, such as determining if a metal weld has cracks.
  • medicine
    , such as detecting cancer in a mammography scan.
  • metallography, such as determining the mineral content of a rock sample.
  • microscopy, such as counting the germs in a swab.
  • optical character recognition, such as automatic license plate detection.
  • remote sensing, such as detecting intruders in a house, and producing land cover/land use maps.[2][3]
  • robotics, such as to avoid steering into an obstacle.
  • security, such as detecting a person's eye color or hair color.

Object-based Image Analysis

Image segmentation during the object base image analysis

Object-Based Image Analysis (OBIA) – also Geographic Object-Based Image Analysis (GEOBIA) – "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".[4]

The two main processes in OBIA are (1) segmentation and (2) classification. Traditional image segmentation is on a per-pixel basis. However, OBIA groups pixels into homogeneous objects. These objects can have different shapes and scale. Objects also have statistics associated with them which can be used to classify objects. Statistics can include geometry, context and texture of image objects. The analyst defines statistics in the classification process to generate land cover

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.

Land cover mapping

Process of land cover mapping using TM images

Land cover and land use change detection using remote sensing and geospatial data provides baseline information for assessing the climate change impacts on habitats and biodiversity, as well as natural resources, in the target areas.

Application of land cover mapping

•Local and regional planning

•Disaster management

•Vulnerability and Risk Assessments

•Ecological management

•Monitoring the effects of climate change

•Wildlife management.

•Alternative landscape futures and conservation

•Environmental forecasting

•Environmental impact assessment

•Policy development

References

  1. ISBN 0470844736.{{cite book}}: CS1 maint: multiple names: authors list (link
    )
  2. doi:10.1093/jpe/rtm005
    .
  3. doi:10.1016/j.jag.2012.11.007
    .
  4. ^ G.J. Hay & G. Castilla: Geographic Object-Based Image Analysis (GEOBIA): A new name for a new discipline. In: T. Blaschke, S. Lang & G. Hay (eds.): Object-Based Image Analysis – Spatial Concepts for Knowledge-Driven Remote Sensing Applications. Lecture Notes in Geoinformation and Cartography, 18. Springer, Berlin/Heidelberg, Germany: 75-89 (2008)

Notes

  • The Image Processing Handbook by John C. Russ, ISBN 0-8493-7254-2 (2006)
  • Image Processing and Analysis - Variational, PDE, Wavelet, and Stochastic Methods by Tony F. Chan and Jianhong (Jackie) Shen, ISBN 0-89871-589-X (2005)
  • Front-End Vision and Multi-Scale Image Analysis by Bart M. ter Haar Romeny, Paperback, ISBN 1-4020-1507-0 (2003)
  • Practical Guide to Image Analysis by J.J. Friel, et al., ASM International, ISBN 0-87170-688-1 (2000).
  • Fundamentals of Image Processing by Ian T. Young, Jan J. Gerbrands, Lucas J. Van Vliet, Paperback, ISBN 90-75691-01-7 (1995)
  • Image Analysis and Metallography edited by P.J. Kenny, et al., International Metallographic Society and ASM International (1989).
  • Quantitative Image Analysis of Microstructures by H.E. Exner & H.P. Hougardy, DGM Informationsgesellschaft mbH, ISBN 3-88355-132-5 (1988).
  • Structure Magazine
  • "Metallographic and Materialographic Specimen Preparation, Light Microscopy, Image Analysis and Hardness Testing", Kay Geels in collaboration with Struers A/S, ASTM International 2006.

External links

Retrieved from "https://en.wikipedia.org/w/index.php?title=Image_analysis&oldid=726180821"