Title :
Detection of digital doctoring in exemplar-based inpainted images
Author :
Wu, Qiong ; Sun, Shao-jie ; Zhu, Wei ; LI, Guo-hui ; Tu, Dan
Author_Institution :
Coll. of Inf. Syst. & Manage., Nat. Univ. of Defense Technol., Changsha
Abstract :
Exemplar-based inpainting technique can be used to remove objects from an image and play visual tricks, which would affect the authenticity of images. In this paper, a blind detection method based on zero-connectivity feature and fuzzy membership is proposed to detect the specific doctoring. Firstly, zero-connectivity labeling is applied on block pairs to yield matching degree feature for all blocks in the region of suspicious, and fuzzy memberships are computed by constructing ascending semi-trapezoid membership function. Then the tampered regions are identified by a cut set. A num of natural and inpainted forged images are used to show the effectiveness of our method in detecting digital doctoring.
Keywords :
feature extraction; fuzzy set theory; image matching; digital doctoring detection; exemplar-based inpainted images; fuzzy membership; image authenticity; semitrapezoid membership function; zero-connectivity features; zero-connectivity labeling; Cybernetics; Digital images; Filling; Forensics; Forgery; Labeling; Machine learning; Machine learning algorithms; Object detection; Sun; Digital doctoring; Exemplar-based inpainting; Fuzzy membership; Zero-connectivity labeling;
Conference_Titel :
Machine Learning and Cybernetics, 2008 International Conference on
Conference_Location :
Kunming
Print_ISBN :
978-1-4244-2095-7
Electronic_ISBN :
978-1-4244-2096-4
DOI :
10.1109/ICMLC.2008.4620591
