Approach of RSOR Algorithm Using HSV Color Model for Nude Detection in Digital Images

This paper analyzes the application of pixel segmentation techniques, the recognition and selection of image regions, as well as the performing of operations on the regions found within the digital images in order to detect nudity. The research aims to develop a software tool capable of nudity detection on digital images. The segmentation in the HSV color model (Hue, Saturation, and Value) to locate and remove the pixels corresponding to human skin is used. The algorithm in Recognition, Selection and Operations in Regions (RSOR), to recognize and separate the region with the highest number of skin pixels within the segmented image (largest region), is proposed. Once selected the largest region, the RSOR algorithm calculates the percentage on the segmented image taken from the original one, and then it calculates the percentage on the largest region, in order to identify whether there is a nude in the image. The criteria for appraising if an image depicts a nude is the following: If the percentage of skin pixels in the segmented image, in comparison to the original image, is less than 25% it is not considered a nude, but if it exceeds this percentage, then, the image is a nude. However, when the percentage of the largest region has been estimated and it amounts to less than 35%, the image is definitely not a nude. The final result is a message that informs the user whether or not the image is a nude. The RSOR algorithm obtains a 4.7% false positive, compared to other systems, and it has shown to possess optimum performance for nudity detection.