No Peeking through My Windows: Conserving Privacy in Personal Drones

TL;DR

This paper introduces a lightweight, real-time privacy-preserving method for personal drones that detects and masks windows and private areas in images to prevent privacy invasion.

Contribution

It presents MASP, a novel fast detection and chaotic scrambling technique for privacy preservation in drone imagery, suitable for edge devices.

Findings

MASP effectively detects window objects in real-time videos.

The method successfully masks private areas to protect individual privacy.

Experimental results confirm MASP's lightweight and real-time performance.

Abstract

The drone technology has been increasingly used by many tech-savvy consumers, a number of defense companies, hobbyists and enthusiasts during the last ten years. Drones often come in various sizes and are designed for a multitude of purposes. Nowadays many people have small-sized personal drones for entertainment, filming, or transporting items from one place to another. However, personal drones lack a privacy-preserving mechanism. While in mission, drones often trespass into the personal territories of other people and capture photos or videos through windows without their knowledge and consent. They may also capture video or pictures of people walking, sitting, or doing private things within the drones' reach in clear form without their go permission. This could potentially invade people's personal privacy. This paper, therefore, proposes a lightweight privacy-preserving-by-design method that prevents drones from peeking through windows of houses and capturing people doing private things at home. It is a fast window object detection and scrambling technology built based on image-enhancing, morphological transformation, segmentation and contouring processes (MASP). Besides, a chaotic scrambling technique is incorporated into it for privacy purpose. Hence, this mechanism detects window objects in every image or frame of a real-time video and masks them chaotically to protect the privacy of people. The experimental results validated that the proposed MASP method is lightweight and suitable to be employed in drones, considered as edge devices.