Please use this identifier to cite or link to this item:
http://hdl.handle.net/10603/336744
Title: | An intelligent statistical algorithms Approach for objectionable image Discretion |
Researcher: | Balamurali R |
Guide(s): | Chandrasekar A |
Keywords: | Engineering and Technology Computer Science Computer Science Information Systems image Discretion statistical algorithms |
University: | Anna University |
Completed Date: | 2020 |
Abstract: | This 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 |
Pagination: | xviii, 122p |
URI: | http://hdl.handle.net/10603/336744 |
Appears in Departments: | Faculty of Information and Communication Engineering |
Files in This Item:
File | Description | Size | Format | |
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01_title.pdf | Attached File | 22.11 kB | Adobe PDF | View/Open |
02_certificates.pdf | 134.81 kB | Adobe PDF | View/Open | |
03_vivaproceedings.pdf | 354.72 kB | Adobe PDF | View/Open | |
04_bonafidecertificate.pdf | 8.79 kB | Adobe PDF | View/Open | |
05_abstracts.pdf | 4.75 kB | Adobe PDF | View/Open | |
06_acknowledgements.pdf | 5.8 kB | Adobe PDF | View/Open | |
07_contents.pdf | 6.14 kB | Adobe PDF | View/Open | |
08_listoftables.pdf | 2.5 kB | Adobe PDF | View/Open | |
09_listoffigures.pdf | 8.74 kB | Adobe PDF | View/Open | |
10_listofabbreviations.pdf | 4.58 kB | Adobe PDF | View/Open | |
11_chapter1.pdf | 41.39 kB | Adobe PDF | View/Open | |
12_chapter2.pdf | 735.3 kB | Adobe PDF | View/Open | |
13_chapter3.pdf | 718.38 kB | Adobe PDF | View/Open | |
14_chapter4.pdf | 224.87 kB | Adobe PDF | View/Open | |
15_chapter5.pdf | 550.86 kB | Adobe PDF | View/Open | |
16_conclusion.pdf | 18.99 kB | Adobe PDF | View/Open | |
17_references.pdf | 31.76 kB | Adobe PDF | View/Open | |
18_listofpublications.pdf | 13.43 kB | Adobe PDF | View/Open | |
80_recommendation.pdf | 56.05 kB | Adobe PDF | View/Open |
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