A Novel Nudity Detection Algorithm for Web and Mobile Application Development

TL;DR

This paper introduces a runtime nudity detection algorithm for web and mobile apps that combines skin pixel analysis and face detection to accurately identify nude images quickly.

Contribution

The paper presents a novel combination of skin color modeling and face detection using Google Vision API for effective nudity detection in real-time applications.

Findings

Skin detection accuracy of 95% with low false positives

Face detection accuracy of 99% in under 1 second

Overall nudity detection accuracy of 95%

Abstract

In our current web and mobile application development runtime nude image content detection is very important. This paper presents a runtime nudity detection method for web and mobile application development. We use two parameters to detect the nude content of an image. One is the number of skin pixels another is face region. A skin color model based on RGB, HSV color spaces are used to detect skin pixels in an image. Google vision api is used to detect the face region. By the percentage of skin regions and face regions an image is identified nude or not. The success of this algorithm exists in detecting skin regions and face regions. The skin detection algorithm can detect skin 95% accurately with a low false-positive rate and the google vision api for web and mobile applications can detect face 99% accurately with less than 1 second time. From the experimental analysis, we have seen that the proposed algorithm can detect 95% percent accurately the nudity of an image.