This work is the first comprehensive review about visual privacy protection.Several categories are established for all of the available privacy protection methods.A review of intelligent monitoring systems that takes privacy into account is provided.An overall vision of the state of the art is given to introduce novel researchers.A critical discussion about relevant key topics and open issues is provided. Recent advances in computer vision technologies have made possible the development of intelligent monitoring systems for video surveillance and ambient-assisted living. By using this technology, these systems are able to automatically interpret visual data from the environment and perform tasks that would have been unthinkable years ago. These achievements represent a radical improvement but they also suppose a new threat to individual's privacy. The new capabilities of such systems give them the ability to collect and index a huge amount of private information about each individual. Next-generation systems have to solve this issue in order to obtain the users' acceptance. Therefore, there is a need for mechanisms or tools to protect and preserve people's privacy. This paper seeks to clarify how privacy can be protected in imagery data, so as a main contribution a comprehensive classification of the protection methods for visual privacy as well as an up-to-date review of them are provided. A survey of the existing privacy-aware intelligent monitoring systems and a valuable discussion of important aspects of visual privacy are also provided.

https://eprints.kingston.ac.uk/31628/1/Florez-Revuelta-F-31628.pdf

Visual privacy protection methods

Image inpainting is an effective method to repair damaged image. In this paper, we mainly studied some typical image inpainting models and analyzed these corresponding repair qualities. Firstly, we studied three typical algorithms based on PDE (Partial Differential Equation) model to repair images whose damaged areas are relative small. And then we studied the image inpainting algorithm based on texture synthesis. This kind of inpainting algorithm is suitable for image with large damaged area. Finally, we studied Criminisi inpainting algorithm based on image segmentation in detail, on which we proposed an improved priority formula image repair algorithm, the simulation results indicate that the improved algorithm of this paper showed better performance in repair quality from both subjective and objective aspects.

Research of image inpainting algorithm based on image segmentation

In this paper, we introduce a novel algorithm for digital inpainting of still images. The problem of image inpainting based on single image and its restoration is proposed. The distortion of images are rectification first dividing all images into different scene planar regions and dismisses the projective distortion, thus the visible information can be directly used. The new problem of image inpainting is how to use the wrapped images to repair reasonably the structure and texture information in the target part of the image. Then a new inpainting algorithm based on a pyramid approach to sub-pixel image fusion based on mutual information is applied to fill the holes. The experiment shows good and harmonious results for the repaired image. Our theory also develops the techniques of image fusion and makes it more practically.

http://ieeexplore.ieee.org/iel5/6088936/6099902/06099907.pdf

Wenjuan Ma

Papers

An effective method for removing large object