Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/68348
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dc.contributor.authorWichan Thumthongen_US
dc.contributor.authorHathaichanok Chompoopuenen_US
dc.contributor.authorPita Jaupunpholen_US
dc.date.accessioned2020-04-02T15:25:19Z-
dc.date.available2020-04-02T15:25:19Z-
dc.date.issued2020-01-01en_US
dc.identifier.issn21945365en_US
dc.identifier.issn21945357en_US
dc.identifier.other2-s2.0-85065927043en_US
dc.identifier.other10.1007/978-3-030-19861-9_13en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85065927043&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/68348-
dc.description.abstract© 2020, Springer Nature Switzerland AG. This article proposes an image processing technique to calculate the histological variables from microscope image of occipital bones for gender determination. Occipital bones are highlighted based on 13 parameters to find out the relationship with the gender of samplings. The samples are 80 images classified into 46 males and 34 females with ages between 25 and 90 years old. Direct and stepwise discriminant functions are two methods for accuracy evaluation. The experiments show demonstrative results of gender determination accuracy based on both direct and stepwise discriminant functions. While the direct discrimination on 5 parameters represents 97.5% for both gender classification and gender prediction, the stepwise discrimination on 3 parameters is also at 97.5% for both gender classification and gender prediction.en_US
dc.subjectComputer Scienceen_US
dc.subjectEngineeringen_US
dc.titleImage Processing Technique for Gender Determination from Medical Microscope Imageen_US
dc.typeBook Seriesen_US
article.title.sourcetitleAdvances in Intelligent Systems and Computingen_US
article.volume936en_US
article.stream.affiliationsRambhai Barni Rajabhat Universityen_US
article.stream.affiliationsPhuket Rajabhat Universityen_US
article.stream.affiliationsChiang Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

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