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http://hdl.handle.net/10603/253042
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DC Field | Value | Language |
---|---|---|
dc.coverage.spatial | Design and development of image Processing methodologies applied Towards human age and gender Estimation | |
dc.date.accessioned | 2019-08-19T12:44:24Z | - |
dc.date.available | 2019-08-19T12:44:24Z | - |
dc.identifier.uri | http://hdl.handle.net/10603/253042 | - |
dc.description.abstract | Detection of facial features for effective face recognition is essential newlinefor achieving security in public gatherings and unique identity of individual newlinehuman faces. Identifying human s facial expressions and face views from the newlineface image is also performed to predict the gender and age of the human newlineadditionally. There are many applications developed in the field of Human newlineFacial Age and Gender classification process. The advantages of all these newlineapplications motivated the direction of this proposed system. Generally, the newlineframe work of Human Facial Age and Gender estimation has three main steps newlinelike Face detection, Gender Detection and Age estimation. newlineMany existing methods are available in the area of Human Facial Age newlineand Gender detection process. Several issues and challenges are observed in newlinethese existing methodologies. The prime focus on this proposed research newlinework is to design and develop an enhanced application of Age estimation and newlineGender detection from facial features. Here, the first stage in the proposed newlinesystem is face detection. This is achieved by Spectral Color Clustered Face newlineDetection (SCC-FD) technique with the help of behavioral patterns in the newlinehuman faces. Face and its characteristic points are positioned based on the newlineobtained skin color features. Followed by the removal ofnon skin color newlineregions, further investigation is continued in the image pixel with skin color. newlineFinally, human face detection is achieved by employing spectral color cluster newlineon the obtained input images where spectral color cluster accuracy and face newlinedetection rate are improved significantly. newline newline | |
dc.format.extent | xxii, 138p. | |
dc.language | English | |
dc.relation | p.129-137 | |
dc.rights | university | |
dc.title | Design and development of image processing methodologies applied towards human age and gender estimation | |
dc.title.alternative | ||
dc.creator.researcher | Berlin jinu C K | |
dc.subject.keyword | human age | |
dc.subject.keyword | image Processing | |
dc.subject.keyword | Social Sciences,Social Sciences General,Family Studies | |
dc.description.note | ||
dc.contributor.guide | Balakrishnan G | |
dc.publisher.place | Chennai | |
dc.publisher.university | Anna University | |
dc.publisher.institution | Faculty of Science and Humanities | |
dc.date.registered | n.d. | |
dc.date.completed | 2018 | |
dc.date.awarded | 30/06/2018 | |
dc.format.dimensions | 21cm | |
dc.format.accompanyingmaterial | None | |
dc.source.university | University | |
dc.type.degree | Ph.D. | |
Appears in Departments: | Faculty of Science and Humanities |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
01_title.pdf | Attached File | 23.85 kB | Adobe PDF | View/Open |
02_certificates.pdf | 60.65 kB | Adobe PDF | View/Open | |
03_abstract.pdf | 66.91 kB | Adobe PDF | View/Open | |
04_acknowledgment.pdf | 5.86 kB | Adobe PDF | View/Open | |
05_contents.pdf | 206.76 kB | Adobe PDF | View/Open | |
06_chapter1.pdf | 190.62 kB | Adobe PDF | View/Open | |
07_chapter2.pdf | 187.63 kB | Adobe PDF | View/Open | |
08_chapter3.pdf | 1.26 MB | Adobe PDF | View/Open | |
09_chapter4.pdf | 682.89 kB | Adobe PDF | View/Open | |
10_chapter5.pdf | 453.93 kB | Adobe PDF | View/Open | |
11_conclusion.pdf | 137.61 kB | Adobe PDF | View/Open | |
12_references.pdf | 159.54 kB | Adobe PDF | View/Open | |
13_publications.pdf | 176.25 kB | Adobe PDF | View/Open |
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