Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/336744
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dc.coverage.spatialAn intelligent statistical algorithms Approach for objectionable image Discretion
dc.date.accessioned2021-08-19T05:08:47Z-
dc.date.available2021-08-19T05:08:47Z-
dc.identifier.urihttp://hdl.handle.net/10603/336744-
dc.description.abstractThis thesis discusses the chances of detecting pictures containing nudity the use of computer algorithms. We have solely focused on sexually pecific images. Our method is to extract points such as skin, faces and regions, which can be used to classify photos which was once carried out in two stages. Initially, we have analyzed and applied a novel method to filter objectionable adult images displayed in websites, as this hassle remains an interesting issue to be addressed in the present day scenario. The algorithm is aimed to gain particular performance, even in exclusive circumstances, where face detection will become impossible. This is realized by using an ancillary method in which the Human Body place is analyzed the use of shape, shade and picture situated pixel scanning analysis. Further a sequence of MATLAB simulation consequences are shown. The consequences of pixel scanning strategy are analyzed and a more suitable integrated filter is designed to improve the performance. Furthermore, we additionally proposed a novel two stage more than one parameter statistical algorithm to identify pornographic images. In this research, we additionally introduced an analysis on quite a number color spaces to discover a most advantageous color space for human pores and skin pixel identification. A new algorithm is proposed to pick out and avoid the specific image through considering high skin pixel rate. The proposed algorithm was once examined in terms of accuracy, genuine negatives and false positives and the experimental consequences show that the algorithm worked well and quick in detecting pornographic images newline
dc.format.extentxviii, 122p
dc.languageEnglish
dc.relationp.113-121
dc.rightsuniversity
dc.titleAn intelligent statistical algorithms Approach for objectionable image Discretion
dc.title.alternative
dc.creator.researcherBalamurali R
dc.subject.keywordEngineering and Technology
dc.subject.keywordComputer Science
dc.subject.keywordComputer Science Information Systems
dc.subject.keywordimage Discretion
dc.subject.keywordstatistical algorithms
dc.description.note
dc.contributor.guideChandrasekar A
dc.publisher.placeChennai
dc.publisher.universityAnna University
dc.publisher.institutionFaculty of Information and Communication Engineering
dc.date.registered
dc.date.completed2020
dc.date.awarded2020
dc.format.dimensions21cm
dc.format.accompanyingmaterialNone
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:Faculty of Information and Communication Engineering

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02_certificates.pdf134.81 kBAdobe PDFView/Open
03_vivaproceedings.pdf354.72 kBAdobe PDFView/Open
04_bonafidecertificate.pdf8.79 kBAdobe PDFView/Open
05_abstracts.pdf4.75 kBAdobe PDFView/Open
06_acknowledgements.pdf5.8 kBAdobe PDFView/Open
07_contents.pdf6.14 kBAdobe PDFView/Open
08_listoftables.pdf2.5 kBAdobe PDFView/Open
09_listoffigures.pdf8.74 kBAdobe PDFView/Open
10_listofabbreviations.pdf4.58 kBAdobe PDFView/Open
11_chapter1.pdf41.39 kBAdobe PDFView/Open
12_chapter2.pdf735.3 kBAdobe PDFView/Open
13_chapter3.pdf718.38 kBAdobe PDFView/Open
14_chapter4.pdf224.87 kBAdobe PDFView/Open
15_chapter5.pdf550.86 kBAdobe PDFView/Open
16_conclusion.pdf18.99 kBAdobe PDFView/Open
17_references.pdf31.76 kBAdobe PDFView/Open
18_listofpublications.pdf13.43 kBAdobe PDFView/Open
80_recommendation.pdf56.05 kBAdobe PDFView/Open


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