It is easy for teenagers to view pornographic pictures on social networks. Many researchers have studied the detection of real pornographic pictures, but there are few studies on those that are artificial. In this wor...It is easy for teenagers to view pornographic pictures on social networks. Many researchers have studied the detection of real pornographic pictures, but there are few studies on those that are artificial. In this work, we studied how to detect artificial pornographic pictures, especially when they are on social networks. The whole detection process can be divided into two stages： feature selection and picture detection. In the feature selection stage, seven types of features that favour picture detection were selected. In the picture detection stage, three steps were included. 1） In order to alleviate the imbalance in the number of artificial pornographic pictures and normal ones, the training dataset of artificial pornographic pictures was expanded. Therefore, the features which were extracted from the training dataset can also be expanded too. 2） In order to reduce the time of feature extraction, a fast method which extracted features based on the proportionally scaled picture rather than the original one was proposed. 3） Three tree models were compared and a gradient boost decision tree （GBDT） was selected for the final picture detection. Three sets of experimental results show that the proposed method can achieve better recognition precision and drastically reduce the time cost of the method.展开更多
A novel approach is proposed to automatically detect pomographic images with skin-like color background on the Intemet using the locations of human faces and bodies. It has two separate skin-color detection steps： th...A novel approach is proposed to automatically detect pomographic images with skin-like color background on the Intemet using the locations of human faces and bodies. It has two separate skin-color detection steps： the first one is to quickly detect the potential human skin-color regions; and the second one is to use an off-the-shelf face detector to locate a human face and then apply hypothesis testing based on series of assumptions which take into account the face-height ratio, body orientation and modem photograph composition common sense, etc. After that, a template matching method is used to further discriminate normal images or pornographic ones. Experimental results show that the proposed method has high precision and real time speed.展开更多
基金Projects(61573380,61303185) supported by the National Natural Science Foundation of ChinaProjects(2016M592450,2017M612585) supported by the China Postdoctoral Science FoundationProjects(2016JJ4119,2017JJ3416) supported by the Hunan Provincial Natural Science Foundation of China
文摘It is easy for teenagers to view pornographic pictures on social networks. Many researchers have studied the detection of real pornographic pictures, but there are few studies on those that are artificial. In this work, we studied how to detect artificial pornographic pictures, especially when they are on social networks. The whole detection process can be divided into two stages： feature selection and picture detection. In the feature selection stage, seven types of features that favour picture detection were selected. In the picture detection stage, three steps were included. 1） In order to alleviate the imbalance in the number of artificial pornographic pictures and normal ones, the training dataset of artificial pornographic pictures was expanded. Therefore, the features which were extracted from the training dataset can also be expanded too. 2） In order to reduce the time of feature extraction, a fast method which extracted features based on the proportionally scaled picture rather than the original one was proposed. 3） Three tree models were compared and a gradient boost decision tree （GBDT） was selected for the final picture detection. Three sets of experimental results show that the proposed method can achieve better recognition precision and drastically reduce the time cost of the method.
文摘A novel approach is proposed to automatically detect pomographic images with skin-like color background on the Intemet using the locations of human faces and bodies. It has two separate skin-color detection steps： the first one is to quickly detect the potential human skin-color regions; and the second one is to use an off-the-shelf face detector to locate a human face and then apply hypothesis testing based on series of assumptions which take into account the face-height ratio, body orientation and modem photograph composition common sense, etc. After that, a template matching method is used to further discriminate normal images or pornographic ones. Experimental results show that the proposed method has high precision and real time speed.
