Hierarchical-Masked Image Filtering for Privacy-Protection

Abstract

SUMMARYThis paper presents a hierarchical-masked image filtering method for privacy-protection. Cameras are widely used for various applications, e.g., crime surveillance, environment monitoring, and marketing. However, invasion of privacy has become a serious social problem, especially regarding the use of surveillance cameras. Many surveillance cameras point at many people; thus, a large amount of our private information of our daily activities are under surveillance. However, several surveillance cameras currently on the market and related research often have a complicated or institutional masking privacy-protection functionality. To overcome this problem, a Hierarchical-Masked image Filtering (HMF) method is proposed, which has unmaskable (mask reversal) capability and is applicable to current surveillance camera systems for privacy-information protection and can satisfy privacy-protection related requirements. This method has five main features: unmasking of the original image from only the masked image and a cipher key, hierarchical-mask level control using parameters for the length of a pseudorandom number, robustness against malicious attackers, fast processing on an embedded processor, and applicability of mask operation to current surveillance camera systems. Previous studies have difficulty in providing these features. To evaluate HMF on actual equipment, an HMF-based prototype system is developed that mainly consists of a USB web camera, ultra-compact single board computer, and notebook PC. Through experiments, it is confirmed that the proposed method achieves mask level control and is robust against attacks. The increase in processing time of the HMF-based prototype system compared with a conventional non-masking system is only about 1.4%. This paper also reports on the comparison of the proposed method with conventional privacy protection methods and favorable responses of people toward the HMF-based prototype system both domestically and abroad. Therefore, the proposed HMF method can be applied to embedded systems such as those equipped with surveillance cameras for protecting privacy.