Obscenity Detection Using Haar-Like Features and Gentle Adaboost Classifier
Large exposure of skin area of an image is considered obscene. This only fact may lead to many false images having skin-like objects and may not detect those images which have partially exposed skin area but have exposed erotogenic human body parts. This paper presents a novel method for detecting n...
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| Format: | Article |
| Language: | English |
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Wiley
2014-01-01
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| Series: | The Scientific World Journal |
| Online Access: | http://dx.doi.org/10.1155/2014/753860 |
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| _version_ | 1832566853401051136 |
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| author | Rashed Mustafa Yang Min Dingju Zhu |
| author_facet | Rashed Mustafa Yang Min Dingju Zhu |
| author_sort | Rashed Mustafa |
| collection | DOAJ |
| description | Large exposure of skin area of an image is considered obscene. This only fact may lead to many false images having skin-like objects and may not detect those images which have partially exposed skin area but have exposed erotogenic human body parts. This paper presents a novel method for detecting nipples from pornographic image contents. Nipple is considered as an erotogenic organ to identify pornographic contents from images. In this research Gentle Adaboost (GAB) haar-cascade classifier and haar-like features used for ensuring detection accuracy. Skin filter prior to detection made the system more robust. The experiment showed that, considering accuracy, haar-cascade classifier performs well, but in order to satisfy detection time, train-cascade classifier is suitable. To validate the results, we used 1198 positive samples containing nipple objects and 1995 negative images. The detection rates for haar-cascade and train-cascade classifiers are 0.9875 and 0.8429, respectively. The detection time for haar-cascade is 0.162 seconds and is 0.127 seconds for train-cascade classifier. |
| format | Article |
| id | doaj-art-c19a14a01ef845bc8285e545c31aee55 |
| institution | Kabale University |
| issn | 2356-6140 1537-744X |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | The Scientific World Journal |
| spelling | doaj-art-c19a14a01ef845bc8285e545c31aee552025-02-03T01:03:11ZengWileyThe Scientific World Journal2356-61401537-744X2014-01-01201410.1155/2014/753860753860Obscenity Detection Using Haar-Like Features and Gentle Adaboost ClassifierRashed Mustafa0Yang Min1Dingju Zhu2Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, ChinaDepartment of Computer Science, The University of Hong Kong, Hong Kong 999077, Hong KongShenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, ChinaLarge exposure of skin area of an image is considered obscene. This only fact may lead to many false images having skin-like objects and may not detect those images which have partially exposed skin area but have exposed erotogenic human body parts. This paper presents a novel method for detecting nipples from pornographic image contents. Nipple is considered as an erotogenic organ to identify pornographic contents from images. In this research Gentle Adaboost (GAB) haar-cascade classifier and haar-like features used for ensuring detection accuracy. Skin filter prior to detection made the system more robust. The experiment showed that, considering accuracy, haar-cascade classifier performs well, but in order to satisfy detection time, train-cascade classifier is suitable. To validate the results, we used 1198 positive samples containing nipple objects and 1995 negative images. The detection rates for haar-cascade and train-cascade classifiers are 0.9875 and 0.8429, respectively. The detection time for haar-cascade is 0.162 seconds and is 0.127 seconds for train-cascade classifier.http://dx.doi.org/10.1155/2014/753860 |
| spellingShingle | Rashed Mustafa Yang Min Dingju Zhu Obscenity Detection Using Haar-Like Features and Gentle Adaboost Classifier The Scientific World Journal |
| title | Obscenity Detection Using Haar-Like Features and Gentle Adaboost Classifier |
| title_full | Obscenity Detection Using Haar-Like Features and Gentle Adaboost Classifier |
| title_fullStr | Obscenity Detection Using Haar-Like Features and Gentle Adaboost Classifier |
| title_full_unstemmed | Obscenity Detection Using Haar-Like Features and Gentle Adaboost Classifier |
| title_short | Obscenity Detection Using Haar-Like Features and Gentle Adaboost Classifier |
| title_sort | obscenity detection using haar like features and gentle adaboost classifier |
| url | http://dx.doi.org/10.1155/2014/753860 |
| work_keys_str_mv | AT rashedmustafa obscenitydetectionusinghaarlikefeaturesandgentleadaboostclassifier AT yangmin obscenitydetectionusinghaarlikefeaturesandgentleadaboostclassifier AT dingjuzhu obscenitydetectionusinghaarlikefeaturesandgentleadaboostclassifier |