Prototype of Pornographic Image Detection with YCbCr and Color Space (RGB) Methods of Computer Vision

An Enhanced Multimodal Stacking Scheme for Online Pornographic Content Detection

“…According to the analysis of the experimental results, the performance rates of the proposed scheme are 95.40%, 92.33%, and 4.60% for the true positive rate, accuracy, and false negative rate, respectively. In recent years, many studies have reported of high performance in the harmful content detections using various deep learning approaches [6][7][8][9][10][11]13,14]. Among the studies, some use video frame image or video clips [7][8][9][10][11], motion analysis [6], or age prediction from facial images [14] as the visual element of input content to determine the harmfulness.…”

“…In recent years, many studies have reported of high performance in the harmful content detections using various deep learning approaches [6][7][8][9][10][11]13,14]. Among the studies, some use video frame image or video clips [7][8][9][10][11], motion analysis [6], or age prediction from facial images [14] as the visual element of input content to determine the harmfulness. When comparing the performance results of these approaches, the approach of [6] with the accuracy rate of 95.1% and the approach of [7] with the true positive rates of 97.52% are showed better performance than the enhanced multimodal stacking scheme suggested in this study.…”

“…When comparing the performance results of these approaches, the approach of [6] with the accuracy rate of 95.1% and the approach of [7] with the true positive rates of 97.52% are showed better performance than the enhanced multimodal stacking scheme suggested in this study. However, since the techniques used in [6][7][8][9][10][11]13,14] cannot properly detect the harmful contents based on the acoustic elements, the proposed scheme in this paper, which includes an auditory element detection, can be evaluated as more advanced.…”

“…Since much of the recent pornographic contents provided through the online personal broadcasting services have harmful scenes either in the form of visual or auditory manner, fast and accurate detection seems vital. However, most previous studies related to the automatic detection of pornographic contents have mainly focused on single modal detection that extracts and uses either visual or auditory features [3][4][5][6][7][8][9][10][11][12][13][14]. One of the limitations of existing methods based on single modal detection approach is that the harmful contents without the detectable elements cannot be detected.…”

“…Recently, to supplement the problems of the existing studies [3][4][5][6][7][8][9][10][11][12][13][14][15][16] and satisfy the requirements of the online harmful content detection, a method that utilizes multiple features extracted from the visual, motion, and auditory elements for the pornographic detections was proposed in [17]. In the detection method proposed in [17], the harmfulness is decided via unit segments that are divided as a particular unit length from the input content.…”