The easy generation, storage, transmission and reproduction of digital images have caused serious abuse and security problems. Assurance of the rightful ownership, integrity, and authenticity is a major concern to the...The easy generation, storage, transmission and reproduction of digital images have caused serious abuse and security problems. Assurance of the rightful ownership, integrity, and authenticity is a major concern to the academia as well as the industry. On the other hand, efficient search of the huge amount of images has become a great challenge. Image hashing is a technique suitable for use in image authentication and content based image retrieval （CBIR）. In this article, we review some representative image hashing techniques proposed in the recent years, with emphases on how to meet the conflicting requirements of perceptual robustness and security. Following a brief introduction to some earlier methods, we focus on a typical two-stage structure and some geometric-distortion resilient techniques. We then introduce two image hashing approaches developed in our own research, and reveal security problems in some existing methods due to the absence of secret keys in certain stage of the image feature extraction, or availability of a large quantity of images, keys, or the hash function to the adversary. More research efforts are needed in developing truly robust and secure image hashing techniques.展开更多
Image hashing is a useful multimedia technology for many applications,such as image authentication,image retrieval,image copy detection and image forensics.In this paper,we propose a robust image hashing based on rand...Image hashing is a useful multimedia technology for many applications,such as image authentication,image retrieval,image copy detection and image forensics.In this paper,we propose a robust image hashing based on random Gabor filtering and discrete wavelet transform(DWT).Specifically,robust and secure image features are first extracted from the normalized image by Gabor filtering and a chaotic map called Skew tent map,and then are compressed via a single-level 2-D DWT.Image hash is finally obtained by concatenating DWT coefficients in the LL sub-band.Many experiments with open image datasets are carried out and the results illustrate that our hashing is robust,discriminative and secure.Receiver operating characteristic(ROC)curve comparisons show that our hashing is better than some popular image hashing algorithms in classification performance between robustness and discrimination.展开更多
It is well known that robustness, fragility, and security are three important criteria of image hashing; however how to build a system that can strongly meet these three criteria is still a challenge. In this paper, a...It is well known that robustness, fragility, and security are three important criteria of image hashing; however how to build a system that can strongly meet these three criteria is still a challenge. In this paper, a content-based image hashing scheme using wave atoms is proposed, which satisfies the above criteria. Compared with traditional transforms like wavelet transform and discrete cosine transform （DCT）, wave atom transform is adopted for the sparser expansion and better characteristics of texture feature extraction which shows better performance in both robustness and fragility. In addition, multi-frequency detection is presented to provide an application-defined trade-off. To ensure the security of the proposed approach and its resistance to a chosen-plaintext attack, a randomized pixel modulation based on the Rdnyi chaotic map is employed, combining with the nonliner wave atom transform. The experimental results reveal that the proposed scheme is robust against content-preserving manipulations and has a good discriminative capability to malicions tampering.展开更多
A lexicographic image hash method based on space and frequency features was proposed. At first, the image database was constructed, and then color and texture features were extracted from the image blocks including in...A lexicographic image hash method based on space and frequency features was proposed. At first, the image database was constructed, and then color and texture features were extracted from the image blocks including information for every image in the database, which formed feature vectors. The feature vectors were clustered to form dictionary. In hash generation, the image was preproc^ssed and divided into blocks firstly. Then color and texture features vectors were extracted from the blocks. These feature vectors were used to search the dictionary, and the nearest word in dictionary for each block was used to form the space features. At the same time. frequency feature was extracted from each block. The space and frequency features were connected to form the intermediate hash. Lastly, the final hash sequence was obtained by pseudo-randomly permuting the intermediate hash. Experiments show that the method has a very low probability of collision and a good perception of robustness. Compared with other methods, this method has a low collision rate.展开更多
In this work, image feature vectors are formed for blocks containing sufficient information, which are selected using a singular-value criterion. When the ratio between the first two SVs axe below a given threshold, t...In this work, image feature vectors are formed for blocks containing sufficient information, which are selected using a singular-value criterion. When the ratio between the first two SVs axe below a given threshold, the block is considered informative. A total of 12 features including statistics of brightness, color components and texture measures are used to form intermediate vectors. Principal component analysis is then performed to reduce the dimension to 6 to give the final feature vectors. Relevance of the constructed feature vectors is demonstrated by experiments in which k-means clustering is used to group the vectors hence the blocks. Blocks falling into the same group show similar visual appearances.展开更多
A color-intensity feature extraction method is proposed aimed at supplementing conventional image hashing algorithms that only consider intensity of the image. An image is mapped to a set of blocks represented by thei...A color-intensity feature extraction method is proposed aimed at supplementing conventional image hashing algorithms that only consider intensity of the image. An image is mapped to a set of blocks represented by their dominant colors and average intensities. The dominant color is defined by hue and saturation with the hue value adjusted to make the principal colors more uniformly distributed. The average intensity is extracted from the Y component in the YCbCr space. By quantizing the color and intensity components, a feature vector is formed in a cylindrical coordinate system for each image block, which may be used to generate an intermediate hash. Euclidean distance is modified and a similarity metric introduced to measure the degree of similarity between images in terms of the color-intensity features. This is used to validate effectiveness of the proposed feature vector. Experiments show that the color-intensity feature is robust to normal image processing while sensitive to malicious alteration, in particular, color modification.展开更多
This paper proposes a verifiable secret image sharing scheme based on compressive sensing, secret sharing, and image hashing. In this scheme, Toeplitz matrix generated by two chaotic maps is employed as measurement ma...This paper proposes a verifiable secret image sharing scheme based on compressive sensing, secret sharing, and image hashing. In this scheme, Toeplitz matrix generated by two chaotic maps is employed as measurement matrix. With the help of Shamir threshold scheme and image hashing, the receivers can obtain the stored values and the hash value of image. In the verifying stage and restoring stage, there must be at least t legal receivers to get the effective information. By comparing the hash value of the restored image with the hash value of original image, the scheme can effectively prevent the attacker from tampering or forging the shared images. Experimental results show that the proposed scheme has good recovery performance, can effectively reduce space, and is suitable for real-time transmission, storage, and verification.展开更多
基金supported by the National Natural Science Foundation of China（Grant No.60502039）,the Shanghai Rising-Star Program（Grant No.06QA14022）,and the Key project of Shanghai Municipality for Basic Research （Grant No.04JC14037）
文摘The easy generation, storage, transmission and reproduction of digital images have caused serious abuse and security problems. Assurance of the rightful ownership, integrity, and authenticity is a major concern to the academia as well as the industry. On the other hand, efficient search of the huge amount of images has become a great challenge. Image hashing is a technique suitable for use in image authentication and content based image retrieval （CBIR）. In this article, we review some representative image hashing techniques proposed in the recent years, with emphases on how to meet the conflicting requirements of perceptual robustness and security. Following a brief introduction to some earlier methods, we focus on a typical two-stage structure and some geometric-distortion resilient techniques. We then introduce two image hashing approaches developed in our own research, and reveal security problems in some existing methods due to the absence of secret keys in certain stage of the image feature extraction, or availability of a large quantity of images, keys, or the hash function to the adversary. More research efforts are needed in developing truly robust and secure image hashing techniques.
基金This work is partially supported by the National Natural Science Foundation of China(Nos.61562007,61762017,61702332)National Key R&D Plan of China(2018YFB1003701)+3 种基金Guangxi“Bagui Scholar”Teams for Innovation and Research,the Guangxi Natural Science Foundation(Nos.2017GXNSFAA198222,2015GXNSFDA139040)the Project of Guangxi Science and Technology(Nos.GuiKeAD17195062)the Project of the Guangxi Key Lab of Multi-source Information Mining&Security(Nos.16-A-02-02,15-A-02-02)the Guangxi Collaborative Innovation Center of Multi-source Information Integration and Intelligent Processing,and the Innovation Project of Guangxi Graduate Education(No.XYCSZ 2018076).
文摘Image hashing is a useful multimedia technology for many applications,such as image authentication,image retrieval,image copy detection and image forensics.In this paper,we propose a robust image hashing based on random Gabor filtering and discrete wavelet transform(DWT).Specifically,robust and secure image features are first extracted from the normalized image by Gabor filtering and a chaotic map called Skew tent map,and then are compressed via a single-level 2-D DWT.Image hash is finally obtained by concatenating DWT coefficients in the LL sub-band.Many experiments with open image datasets are carried out and the results illustrate that our hashing is robust,discriminative and secure.Receiver operating characteristic(ROC)curve comparisons show that our hashing is better than some popular image hashing algorithms in classification performance between robustness and discrimination.
文摘It is well known that robustness, fragility, and security are three important criteria of image hashing; however how to build a system that can strongly meet these three criteria is still a challenge. In this paper, a content-based image hashing scheme using wave atoms is proposed, which satisfies the above criteria. Compared with traditional transforms like wavelet transform and discrete cosine transform （DCT）, wave atom transform is adopted for the sparser expansion and better characteristics of texture feature extraction which shows better performance in both robustness and fragility. In addition, multi-frequency detection is presented to provide an application-defined trade-off. To ensure the security of the proposed approach and its resistance to a chosen-plaintext attack, a randomized pixel modulation based on the Rdnyi chaotic map is employed, combining with the nonliner wave atom transform. The experimental results reveal that the proposed scheme is robust against content-preserving manipulations and has a good discriminative capability to malicions tampering.
基金Natural Science Foundations of Shanghai,China(Nos.15ZR1418500,15ZR1418400)the Training Program of Shanghai University of Electric Power for Academic Backbone Teachers,China
文摘A lexicographic image hash method based on space and frequency features was proposed. At first, the image database was constructed, and then color and texture features were extracted from the image blocks including information for every image in the database, which formed feature vectors. The feature vectors were clustered to form dictionary. In hash generation, the image was preproc^ssed and divided into blocks firstly. Then color and texture features vectors were extracted from the blocks. These feature vectors were used to search the dictionary, and the nearest word in dictionary for each block was used to form the space features. At the same time. frequency feature was extracted from each block. The space and frequency features were connected to form the intermediate hash. Lastly, the final hash sequence was obtained by pseudo-randomly permuting the intermediate hash. Experiments show that the method has a very low probability of collision and a good perception of robustness. Compared with other methods, this method has a low collision rate.
基金Project supported by the National Natural Science Foundation of China （Grant No.60502039）, the Shanghai Rising-Star Program （Grant No.06QA14022）, and the Key Project of Shanghai Municipality for Basic Research （Grant No.04JC14037）
文摘In this work, image feature vectors are formed for blocks containing sufficient information, which are selected using a singular-value criterion. When the ratio between the first two SVs axe below a given threshold, the block is considered informative. A total of 12 features including statistics of brightness, color components and texture measures are used to form intermediate vectors. Principal component analysis is then performed to reduce the dimension to 6 to give the final feature vectors. Relevance of the constructed feature vectors is demonstrated by experiments in which k-means clustering is used to group the vectors hence the blocks. Blocks falling into the same group show similar visual appearances.
基金Project supported by the National Natural Science Foundation of China (Grant Nos.60773079, 60872116, 60832010)the National High-Technology Research and Development Program of China (Grant No.2007AA01Z477)
文摘A color-intensity feature extraction method is proposed aimed at supplementing conventional image hashing algorithms that only consider intensity of the image. An image is mapped to a set of blocks represented by their dominant colors and average intensities. The dominant color is defined by hue and saturation with the hue value adjusted to make the principal colors more uniformly distributed. The average intensity is extracted from the Y component in the YCbCr space. By quantizing the color and intensity components, a feature vector is formed in a cylindrical coordinate system for each image block, which may be used to generate an intermediate hash. Euclidean distance is modified and a similarity metric introduced to measure the degree of similarity between images in terms of the color-intensity features. This is used to validate effectiveness of the proposed feature vector. Experiments show that the color-intensity feature is robust to normal image processing while sensitive to malicious alteration, in particular, color modification.
基金Supported by the National Natural Science Foundation of China(61572089,61502399)the Natural Science Foundation of Chongqing Science and Technology Commission(cstc2017jcyj BX0008,cstc2015jcyj A40039)+2 种基金the Fundamental Research Funds for the Central Universities(106112017 CDJQJ188830,106112017CDJXY180005,106112014CDJZR185501)the Research Program of Chongqing Education Commission(JK15012027,JK1601225)the Scientific Research Project of Yangtze Normal University(2015XJXM39,2015XJXM31)
文摘This paper proposes a verifiable secret image sharing scheme based on compressive sensing, secret sharing, and image hashing. In this scheme, Toeplitz matrix generated by two chaotic maps is employed as measurement matrix. With the help of Shamir threshold scheme and image hashing, the receivers can obtain the stored values and the hash value of image. In the verifying stage and restoring stage, there must be at least t legal receivers to get the effective information. By comparing the hash value of the restored image with the hash value of original image, the scheme can effectively prevent the attacker from tampering or forging the shared images. Experimental results show that the proposed scheme has good recovery performance, can effectively reduce space, and is suitable for real-time transmission, storage, and verification.
