Detection of inappropriate images on smartphones based on computer vision techniques
Authors: Daisy Imbaquingo, Macarthur Ortega-Bustamante, José Jácome, Tatyana Saltos-Echeverria, Roger Vaca
Abstract: In recent years, the use of smartphones in children and adolescents has increased by a considerable number and, therefore, the dangers faced by this population are increasing. Due to this, it is important to develop a technological solution that allows combat this problem by making use of computer vision. Through a bibliographic review, it has been detected those children and adolescents frequently view violent and pornographic images, this allowed us to build a dataset of this type of images to develop an artificial intelligence model. It was successfully developed under the training and validation phases using a google supercomputer (Google Colab), while for the testing phase it was implemented on an android mobile device, using screenshots, images were extracted that the screen projected, and thus later the results were analyzed under statistics using R studio. The computational model detected, with a large percentage of true positives, images and videos of a pornographic and violent nature captured from the screen resolution of a smartphone while the user was using it normally.
Keywords: Computer vision, risks on internet, violent images, mobile application, parental control
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