SSL: A Novel Image Hashing Technique Using SIFT Keypoints with Saliency Detection and LBP Feature Extraction against Combinatorial Manipulations

Mingfu Xue,Chengxiang Yuan,Zhe Liu,Jian Wang

doi:10.1155/2019/9795621

Abstract

Image hashing schemes have been widely used in content authentication, image retrieval, and digital forensic. In this paper, a novel image hashing algorithm (SSL) by incorporating the most stable keypoints and local region features is proposed, which is robust against various content-preserving manipulations, even multiple combinatorial manipulations. The proposed algorithm combines S_cale invariant feature transform (SIFT) with S_aliency detection to extract the most stable keypoints. Then, the L_ocal binary pattern (LBP) feature extraction method is exploited to generate local region features based on these keypoints. After that, the information of keypoints and local region features are merged into a hash vector. Finally, a secret key is used to randomize the hash vector, which can prevent attackers from forging the image and the hash value. Experimental results demonstrate that the proposed hashing algorithm can identify visually similar images which are under both single and combinatorial content-preserving manipulations, even multiple combinations of manipulations. It can also identify maliciously forged images which are under various content-changing manipulations. The collision probability between hashes of different images is nearly zero. Besides, the evaluation of key-dependent security shows that the proposed scheme is secure that an attacker cannot forge or estimate the correct hash value without the knowledge of the secret key.

Highlights

Due to the wide application of digital image processing technology, the image data protection has raised serious concerns
Image hashing is a technique that extracts a content-based compact signature from an image. It has been effectively applied in content authentication [1,2,3,4,5], digital forensic [6, 7], and image retrieval [8, 9]
(4) Collision resistance: the image hashes of perceptually different images should be different, and different images can be distinguished by hash distances

Summary

Introduction

Due to the wide application of digital image processing technology, the image data protection has raised serious concerns. The proposed scheme extracts the most stable keypoints and texture features from an image to generate image hash, which can resist both single content-preserving manipulation and multiple combinatorial manipulations. (i) The proposed scheme extracts most stable keypoints by exploiting SIFT with saliency detection, which are robust to single content-preserving manipulations and to combinatorial manipulations, even their multiple combinations. These extracted keypoints contain sufficient image information, such as geometric information and descriptors of keypoints, and texture features around the keypoints. By incorporating the most stable keypoints and local texture features, the proposed scheme is sensitive to content-changing manipulations and can locate the tampered regions during the image authentication process.

Related Work

Preliminary

Proposed Image Hashing Scheme

Preprocess

Experimental Results

Conclusion