Content deleted Content added
m Open access bot: doi added to citation with #oabot. |
Aadirulez8 (talk | contribs) m v2.05 - auto / Fix errors for CW project (Link equal to linktext) |
||
| (28 intermediate revisions by 17 users not shown) | |||
Line 2:
{{distinguish|Image processing}}
{{no footnotes|article|date=September 2013}}
'''Image analysis''' is the extraction of meaningful information from [[image]]s; mainly from [[digital image]]s by means of [[digital image processing]] techniques.<ref name="solomonbreckon10fundamentals">{{cite book| author=Solomon, C.J., Breckon, T.P.| title=Fundamentals of Digital Image Processing: A Practical Approach with Examples in Matlab| year=2010| publisher=Wiley-Blackwell| doi=10.1002/9780470689776| isbn=978-0470844731}}</ref> Image analysis tasks can be as simple as reading [[barcode|bar code]]d tags or as sophisticated as [[facial recognition system|identifying a person from their face]].▼
▲'''Image analysis''' or '''imagery analysis''' is the extraction of meaningful information from [[image]]s; mainly from [[digital image]]s by means of [[digital image processing]] techniques.<ref name="solomonbreckon10fundamentals">{{cite book| author=Solomon, C.J., Breckon, T.P.| title=Fundamentals of Digital Image Processing: A Practical Approach with Examples in Matlab| year=2010| publisher=Wiley-Blackwell| doi=10.1002/9780470689776| isbn=978-0470844731}}</ref> Image analysis tasks can be as simple as reading [[barcode|bar code]]d tags or as sophisticated as [[facial recognition system|identifying a person from their face]].
[[Computer]]s 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 detection|edge detectors]] and [[neural networks]] are inspired by human [[visual perception]] models.▼
▲[[Computer]]s 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 detection|edge detectors]] and [[Artificial neural network|neural networks]] are inspired by human [[visual perception]] models.
==Digital==
Line 15 ⟶ 16:
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:
* 2D and 3D [[object recognition]],
* [[
* [[motion detection]] e.g. [[Single particle tracking]],
* [[video tracking]],
* [[optical flow]],
* [[Medical imaging|medical scan analysis]],
* [[3D Pose Estimation]]
* [[automatic number plate recognition]].▼
==Applications==
The applications of digital image analysis are continuously expanding through all areas of science and industry, including:
*[[anatomy]], allows for precise measurements, visualization, and statistical analysis of anatomical structures.<ref>{{Cite journal |last1=Kędzia |first1=Alicja |last2=Derkowski |first2=Wojciech |date=2024 |title=Modern methods of neuroanatomical and neurophysiological research |journal=MethodsX |publication-date=2024 |volume=13 |pages=102881 |doi=10.1016/j.mex.2024.102881 |issn=2215-0161 |pmc=11340600 |pmid=39176151}}</ref>
*[[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.
*[[automated species identification]] (e.g. plant and animal species)
*[[defense (military)|defense]]
*[[error level analysis]]
Line 35 ⟶ 37:
*[[metallography]], such as determining the mineral content of a rock sample.
*[[microscope image processing|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.<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|doi-access=free}}</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|issue=100|pages=81–94|doi=10.1016/j.jag.2012.11.007|pmid=24817838|pmc=4010295|bibcode=2013IJAEO..23...81W}}</ref>
*[[robotics]], such as to avoid steering into an obstacle.
*[[security]], such as detecting a person's eye color or hair color. <!-- get more specific links: fingerprints, face recog, iris, surveillance, license plate-->
==Object-based==
[[File:Object based image analysis.jpg|thumb|Image segmentation during the
object base image analysis]]
'''Object-based image analysis''' ('''OBIA''') involves two typical processes, segmentation and classification. Segmentation helps to group pixels into homogeneous objects. The objects typically correspond to individual features of interest, although over-segmentation or under-segmentation is very likely. Classification then can be performed at object levels, using various statistics of the objects as features in the classifier. Statistics can include geometry, context and texture of image objects. Over-segmentation is often preferred over under-segmentation when classifying high-resolution images.<ref name="liu2018">{{cite journal |last1=Liu |first1=Dan |last2=Toman |first2=Elizabeth |last3=Fuller |first3=Zane |last4=Chen |first4=Gang |last5=Londo |first5=Alexis |last6=Xuesong |first6=Zhang |last7=Kaiguang |first7=Zhao |title=Integration of historical map and aerial imagery to characterize long-term land-use change and landscape dynamics: An object-based analysis via Random Forests |journal=Ecological Indicators |date=2018 |volume=95 |issue=1 |pages=595–605 |doi=10.1016/j.ecolind.2018.08.004 |bibcode=2018EcInd..95..595L |s2cid=92025959 |url=https://pages.charlotte.edu/gang-chen/wp-content/uploads/sites/184/2018/08/Liu_2018_Intigration-historical-map-aerial-imagery-LCLUC.pdf}}</ref>
Object-based image analysis
{{anchor|GEOBIA}}When applied to earth images, OBIA is known as ''Geographic Object-Based Image Analysis'' (GEOBIA), defined as "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".<ref>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)</ref>▼
▲{{anchor|GEOBIA}}When applied to [[earth
▲Object-based image analysis is also applied in other fields, such as cell biology or medicine. It can for instance detect changes of cellular shapes in the process of cell differentiation.<ref>{{Cite journal|last=Salzmann|first=M.|last2=Hoesel|first2=B.|last3=Haase|first3=M.|last4=Mussbacher|first4=M.|last5=Schrottmaier|first5=W. C.|last6=Kral-Pointner|first6=J. B.|last7=Finsterbusch|first7=M.|last8=Mazharian|first8=A.|last9=Assinger|first9=A.|date=2018-02-20|title=A novel method for automated assessment of megakaryocyte differentiation and proplatelet formation|journal=Platelets|volume=29|issue=4|pages=357–364|doi=10.1080/09537104.2018.1430359|issn=1369-1635|pmid=29461915|url=https://research.birmingham.ac.uk/portal/files/48276169/A_novel_method_for_automated_assessment_of_megakaryocyte_differentiation_and_proplatelet_formation.pdf}}</ref>
The international GEOBIA conference has been held biannually since 2006.<ref>{{cite web| url = http://www.mdpi.com/journal/remotesensing/special_issues/geobia| url-status = dead| archive-url = https://web.archive.org/web/20131212125952/http://www.mdpi.com/journal/remotesensing/special_issues/geobia| archive-date = 2013-12-12| title = Remote Sensing {{!}} Special Issue: Advances in Geographic Object-Based Image Analysis (GEOBIA)}}</ref>
OBIA techniques are implemented in software such as [[eCognition]] or the [[Orfeo toolbox]].
== Land cover mapping ==▼
==See also==
Line 72 ⟶ 60:
*[[Imaging technologies]]
*[[Image processing]]
*[[imc FAMOS]] (1987), graphical data analysis
*[[Military intelligence]]
*[[Remote sensing]]
Line 87 ⟶ 77:
* ''Quantitative Image Analysis of Microstructures'' by H.E. Exner & H.P. Hougardy, DGM Informationsgesellschaft mbH, {{ISBN|3-88355-132-5}} (1988).
* "Metallographic and Materialographic Specimen Preparation, Light Microscopy, Image Analysis and Hardness Testing", Kay Geels in collaboration with Struers A/S, ASTM International 2006.
{{Authority control}}
| |||