Robust image hashing based on color vector angle and Canny operator

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• 作者：Zhenjun Tang^a ; ^b ; ^{tangzj230@163.com" class="auth_mail" title="E-mail the corresponding author}Author Vitae ; Liyan Huang^a ; ^bAuthor Vitae ; Xianquan Zhang^a ; ^bAuthor Vitae ; Huan Lao^a ; ^bAuthor Vitae
• 关键词：Image hashing ; Color vector angle ; Image edge ; Canny operator
• 刊名：AEU - International Journal of Electronics and Communications
• 出版年：2016
• 出版时间：June 2016
• 年：2016
• 卷：70
• 期：6
• 页码：833-841
• 全文大小：2738 K

文摘

Image hashing is a novel technology of multimedia processing, and finds many applications, such as image forensics, image retrieval and image indexing. Conventional image hashing algorithms have limitations in reaching desirable classification performances between rotation robustness and discrimination. Aiming at this issue, we propose a robust image hashing based on color vector angle and Canny operator. Specifically, our hashing firstly converts input image to a normalized image by interpolation and Gaussian low-pass filtering. And then, color vector angles and image edges are both extracted from the normalized image. Finally, statistical features incorporating color vector angles and image edges are calculated to form image hash. We conduct experiments with 2762 images to validate efficiency of our hashing. The experimental results show that our hashing is robust against normal digital processing, such as image rotation, brightness/contrast adjustment and JPEG compression, and reaches good discrimination. Receiver operating characteristics (ROC) curve comparisons with some state-of-the-art algorithms indicate that our hashing outperforms these compared algorithms in classification performances between robustness and discriminative capability.