Privacy Protection Filter using StegoScrambling in Video Surveillance

Natacha Ruchaud and Jean-Luc DugelaySpeaker : Natacha Ruchaud

Privacy Filters in Video Surveillance

PRIVACY

PLEASENTNESS

INTELLIGIBILITY

2/15

Main objectives :

No more possibility to recognize people

Trade-of

Good looking

Visual quality, still recognize events: people walking, running, fighting, stealing….

Privacy Filters in Video Surveillance

Time consuming

Reversibility

Flexibility

3/15

But also :

Videos surveillance in real time

Re identification in case of trouble

No need to adapt parameters

Main idea

●Scrambling to protect data●Steganography to hide the protected data in an edge map which preserves global shape and boundary appearance

●Near lossless Reversibility

4/15

Main idea5/15

Edge mapScrambled RoI

Original RoI

StegoScrambled RoI

Crop ConvexHull

Scrambling6/15

Pixel can be represented in 8 bitsRemove the 2 Least significant bits of

the RoIAn XOR between the 6 bits of the RoI

and the random numbers generated with a pseudo-random number controlled by a seed.

Edge map7/15

Edge map8/15

DilatationKmeans ClusteringOriginal RoI

Edges detection AND

Steganography9/15

The 6 bits of the XOR image (pixels intensity is either 0 or 63) are shifted in the LSBs

The 2 MSBs of the edge map (pixels intensity is either 0 or 192) are added in the 2 MSBs of the XOR image

Recovered image10/15

Flowchart11/15

Results12/15

Results13/15

Future works & Perspectives

Less favorable outcome for intelligibility and pleasantness●Edges detector and Kmeans clustering distortions●Black and white results

Future works:

●Improve edges detection●New edge map

14/15

THANK YOU

15/15