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[[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 |page=595-605 |doi=10.1016/j.ecolind.2018.08.004 |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 has been applied in many fields, such as cell biology, medicine, earth sciences, and remote sensing. For example, it can detect changes of cellular shapes in the process of cell differentiation.<ref>{{Cite journal|last1=Salzmann|first1=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|s2cid=3785563|url=https://research.birmingham.ac.uk/portal/files/48276169/A_novel_method_for_automated_assessment_of_megakaryocyte_differentiation_and_proplatelet_formation.pdf|doi-access=free}}</ref>; it has also been widely used in the mapping community to generate [[land cover]].<ref name="liu2018"></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>
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