Fractal Coding-Based Robust and Alignment-Free Fingerprint Image Hashing

Abdullahi, Sani M.; Wang, Hongxia; Тао, Ли

doi:10.1109/tifs.2020.2971142

Cited by 55 publications

(22 citation statements)

References 43 publications

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“…Main techniques [18] Sensitive SIFT + DWT [19] Sensitive SVD + CVA [20] Sensitive LBP + DCT + DWT [21] Sensitive Canny edge + DCT [25] Sensitive QLRBP + mean pooling [27] Within 5°RT + DWT + DFT [28] Within 5°RT + DCT [29] Within 5°ZMs + salient map [30] Within 5°SVD + LBP [31] Within 10°LRSD + CS [33] Within 5°Canny edge + DWT [35] Within 10°Hu moments + DCT [36] Within 10°GLCM + DCT [39] Within 5°QSVD + PCS [40] Within 5°2D PCA + salient map [43] arbitrarily angle Visual model + SIFT [46] arbitrarily angle CVA + DCT [47] arbitrarily angle RP + entropy [48] arbitrarily angle MDS + LPT [51] arbitrarily angle DCT + DNS [52] arbitrarily angle FMT + fractal coding [53] arbitrarily angle KAZE feature + SVD…”

Section: Methods Rotation Robustnessmentioning

confidence: 99%

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Efficient Hashing Method Using 2D-2D PCA for Image Copy Detection

Liang

Tang

Huang

et al. 2023

IEEE Trans. Knowl. Data Eng.

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Image copy detection is an important technology of copyright protection. This paper proposes an efficient hashing method for image copy detection using 2D-2D (two-directional two-dimensional) PCA (Principal Component Analysis). The key is the discovery of the translation invariance of 2D-2D PCA. With the property of translation invariance, a novel model of extracting rotation-invariant lowdimensional features is designed by combining PCT (Polar Coordinate Transformation) and 2D-2D PCA. The PCT can convert an input rotated image to a translation matrix. Since the 2D-2D PCA is invariant to translation, the low-dimensional features learned from the translation matrix are rotation-invariant. Moreover, vector distances of low-dimensional features are stable to common digital operations and thus hash construction with the vector distances is of robustness and compactness. Three open image datasets are exploited to conduct various experiments for validating efficiencies of the proposed method. The results demonstrate that the proposed method is much better than some representative hashing methods in the performances of classification and copy detection.

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Section: Methods Rotation Robustnessmentioning

confidence: 99%

“…Biswas's method can be used for recognizing Tor domains, but the time complexity is too high. Abdullahi et al [52] combined FMT and fractal coding to devise a novel hashing method. Abdullahi's method is stable to rotation and has low time complexity.…”

Section: Related Workmentioning

confidence: 99%

Efficient Hashing Method Using 2D-2D PCA for Image Copy Detection

Liang

Tang

Huang

et al. 2023

IEEE Trans. Knowl. Data Eng.

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“…[23] D W T + CVA 2014 [27] S V D + CVA 2017 [30] Canny operator + DCT 2019 [31] R P + visual salient region 2019 [33] F M T + fractal coding 2020 [34] G T E + DNS 2020 [35] V i s u a l m o d e l + Zernike moments + DCT 2020 [36] S V D + KAZE feature 2021 [37] G L C M + DCT 2021 selected robust features by combining the Canny edge operator and DCT coefficients to calculate a hash. This hashing scheme has a good application on industrial surveillance images, but it is only robust to a small number of digital operations.…”

Section: Methodsmentioning

confidence: 99%

“…This scheme is resistant to large angle rotations, but its classification performance needs to be improved. The FMT and fractal coding technology are joined to construct a new scheme in the reference [33]. This hashing scheme has favorable robustness, but there is still room for improving discrimination.…”

Section: Methodsmentioning

confidence: 99%

A novel hashing scheme via image feature map and 2D PCA

Liang

Tang

Sheng

et al. 2022

IET Image Processing

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Hashing scheme is a high‐efficiency technique for processing massive images. Two critical metrics of the hashing scheme are discrimination and robustness, but most schemes do not get satisfied classification performance between them. This paper proposes a novel hashing scheme via image feature map and 2D PCA. First, the proposed scheme extracts local phase quantization (LPQ) features in the frequency domain and local ternary pattern (LTP) features in the spatial domain, and combines them to construct an image feature map. Second, the proposed scheme conducts dimension reduction via 2D PCA for learning features from the image feature map. Last, the learned features are compressed to generate the hash sequence. Performances are tested on open image datasets. The results demonstrate that the proposed scheme can make a good balance between discrimination and robustness. In addition, the classification and copy detection of the proposed scheme are both superior to those of some famous hashing schemes.

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“…The SC-IoM method extracts the largest and second largest indices of user-specific randomly projected features and uses a large number of hash functions to obtain satisfactory authentication performance. Abdullahi et al [ 18 ] introduced a cancelable fingerprint hash scheme based on the Fourier-Mellin transform and fractal coding. The proposed method performs well over fingerprint databases of reasonably good image quality, but its performance deteriorates when the quality of fingerprint images is poor.…”

Section: Related Workmentioning

confidence: 99%

A Secure Online Fingerprint Authentication System for Industrial IoT Devices over 5G Networks

Bedari

Wang

Yang

2022

Sensors

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The development of 5G networks has rapidly increased the use of Industrial Internet of Things (IIoT) devices for control, monitoring, and processing purposes. Biometric-based user authentication can prevent unauthorized access to IIoT devices, thereby safeguarding data security during production. However, most biometric authentication systems in the IIoT have no template protection, thus risking raw biometric data stored as templates in central databases or IIoT devices. Moreover, traditional biometric authentication faces slow, limited database holding capacity and data transmission problems. To address these issues, in this paper we propose a secure online fingerprint authentication system for IIoT devices over 5G networks. The core of the proposed system is the design of a cancelable fingerprint template, which protects original minutia features and provides privacy and security guarantee for both entity users and the message content transmitted between IIoT devices and the cloud server via 5G networks.Compared with state-of-the-art methods, the proposed authentication system shows competitive performance on six public fingerprint databases, while saving computational costs and achieving fast online matching.

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Fractal Coding-Based Robust and Alignment-Free Fingerprint Image Hashing

Cited by 55 publications

References 43 publications

Efficient Hashing Method Using 2D-2D PCA for Image Copy Detection

Efficient Hashing Method Using 2D-2D PCA for Image Copy Detection

A novel hashing scheme via image feature map and 2D PCA

A Secure Online Fingerprint Authentication System for Industrial IoT Devices over 5G Networks

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