Detection of nudity in photos and videos, especially prior to uploading to the internet, is vital to solving many problems related to adolescent sexting, the distribution of child pornography, and cyber-bullying. The problem with using nudity detection algorithms as a means to combat these problems is that: 1) it implies that a digitized nude photo of a minor already exists (i.e., child pornography), and 2) there are real ethical and legal concerns around the distribution and processing of child pornography. Once a camera captures an image, that image is no longer secure. Therefore, we need to develop new privacy-preserving solutions that prevent the digital capture of nude imagery of minors. My research takes a first step in trying to accomplish this long-term goal: In this thesis, I examine the feasibility of using a low-powered sensor to detect skin dominance (defined as an image comprised of 50% or more of human skin tone) in a visual scene. By designing four custom light filters to enhance the digital information extracted from 300 scenes captured with the sensor (without digitizing high-fidelity visual features), I was able to accurately detect a skin dominant scene with 83.7% accuracy, 83% precision, and 85% recall. The long-term goal to be achieved in the future is to design a low-powered vision sensor that can be mounted on a digital camera lens on a teen's mobile device to detect and/or prevent the capture of nude imagery. Thus, I discuss the limitations of this work toward this larger goal, as well as future research directions.
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Master of Science (M.S.)
College of Engineering and Computer Science
Length of Campus-only Access
Masters Thesis (Open Access)
Tariq, Muhammad Uzair, "Designing Light Filters to Detect Skin Using a Low-powered Sensor" (2017). Electronic Theses and Dissertations. 5512.
Restricted to the UCF community until August 2017; it will then be open access.