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*[[automatic number plate recognition]];
*[[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-->
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''Object-Based Image Analysis'' (OBIA) employs two main processes, segmentation and 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 for example [[land cover]].
{{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><ref name="Blaschke Hay Kelly Lang 2014 pp. 180–191">{{cite journal | last1=Blaschke | first1=Thomas | last2=Hay | first2=Geoffrey J. | last3=Kelly | first3=Maggi | last4=Lang | first4=Stefan | last5=Hofmann | first5=Peter | last6=Addink | first6=Elisabeth | last7=Queiroz Feitosa | first7=Raul | last8=van der Meer | first8=Freek | last9=van der Werff | first9=Harald | last10=van Coillie | first10=Frieke | last11=Tiede | first11=Dirk | title=Geographic Object-Based Image Analysis – Towards a new paradigm | journal=ISPRS Journal of Photogrammetry and Remote Sensing | publisher=Elsevier BV | volume=87 | year=2014 | issue=100 | issn=0924-2716 | doi=10.1016/j.isprsjprs.2013.09.014 | pages=180–191| pmid=24623958 | pmc=3945831 | bibcode=2014JPRS...87..180B | doi-access=free }}</ref>
The international GEOBIA conference has been held biannually since 2006.<ref>[http://www.mdpi.com/journal/remotesensing/special_issues/geobia]</ref>
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