Privacy Protection Performance of De-identified Face Images with and without Background

Sun, Zongji, Meng, Li, Ariyaeeinia, Aladdin, Duan, Xiaodong and Tan, Zheng-Hua (2016) Privacy Protection Performance of De-identified Face Images with and without Background. In: 39th Intl. ICT (Information and Communication Technology) Convention MIPRO 2016 :. Institute of Electrical and Electronics Engineers (IEEE), HRV, p. 1354. ISBN 978-953-233-088-5
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This paper presents an approach to blending a de-identified face region with its original background, for the purpose of completing the process of face de-identification. The re-identification risk of the de-identified FERET face images has been evaluated for the k-Diff-furthest face de-identification method, using several face recognition benchmark methods including PCA, LBP, HOG and LPQ. The experimental results show that the k-Diff-furthest face de-identification delivers high privacy protection within the face region while blending the de-identified face region with its original background may significantly increases the re-identification risk, indicating that de-identification must also be applied to image areas beyond the face region.


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