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'''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 [[Artificial neural network|neural networks]] are inspired by human [[visual perception]] models.
==Digital==
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==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.
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*[[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>
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>▼
{{anchor|GEOBIA}}When applied to [[earth image]]s, 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><ref name="Blaschke Hay Kelly Lang 2014 pp. 180–191" />
▲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)}}
==See also==
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