TY - JOUR ID - 438 TI - Image authentication using LBP-based perceptual image hashing JO - Journal of AI and Data Mining JA - JADM LA - en SN - 2322-5211 AU - Davarzani, R. AU - Mozaffari, S. AU - Yaghmaie, Kh. AD - Department of Electrical and Computer Engineering, College of Engineering, Shahrood Branch, Islamic Azad University, Shahrood, Iran AD - Faculty of Electrical and Computer Engineering, Semnan University, Semnan, Iran. Y1 - 2015 PY - 2015 VL - 3 IS - 1 SP - 21 EP - 30 KW - Center-symmetric local binary patterns KW - perceptual image hashing KW - image authentication KW - tamper detection DO - 10.5829/idosi.JAIDM.2015.03.01.03 N2 - Feature extraction is a main step in all perceptual image hashing schemes in which robust features will led to better results in perceptual robustness. Simplicity, discriminative power, computational efficiency and robustness to illumination changes are counted as distinguished properties of Local Binary Pattern features. In this paper, we investigate the use of local binary patterns for perceptual image hashing. In feature extraction, we propose to use both sign and magnitude information of local differences. So, the algorithm utilizes a combination of gradient-based and LBP-based descriptors for feature extraction. To provide security needs, two secret keys are incorporated in feature extraction and hash generation steps. Performance of the proposed hashing method is evaluated with an important application in perceptual image hashing scheme: image authentication. Experiments are conducted to show that the present method has acceptable robustness against perceptual content-preserving manipulations. Moreover, the proposed method has this capability to localize the tampering area, which is not possible in all hashing schemes. UR - https://jad.shahroodut.ac.ir/article_438.html L1 - https://jad.shahroodut.ac.ir/article_438_f52baa7b766bb4c5418b44d4d9f67a9b.pdf ER -