Optical selective encryption based on the FRFCM algorithm and face biometric for the medical image

Shen, Yuxin; Tang, Chen; Xu, Min; Lei, Zhenkun

doi:10.1016/j.optlastec.2020.106911

Cited by 33 publications

(8 citation statements)

References 32 publications

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“…To isolate the lung from the background, the images were segmented using snake optimization. The proposed approach was compared with three fuzzy-based clustering methods, FCM [ 10 ], KFCM [ 16 ], SAFCM [ 14 ] and FRFCM [ 62 ] based on two metrics: intersection over union (IoU) [ 58 ] and Hausdorff distance. Figure 8 indicates examples of lungs segmented by the Snake algorithm.…”

Section: Empirical Evaluationsmentioning

confidence: 99%

A GAN-based method for 3D lung tumor reconstruction boosted by a knowledge transfer approach

Rezaei

Ahmadi

2023

Multimed Tools Appl

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Three-dimensional (3D) image reconstruction of tumors has been one of the most effective techniques for accurately visualizing tumor structures and treatment with high resolution, which requires a set of two-dimensional medical images such as CT slices. In this paper we propose a novel method based on generative adversarial networks (GANs) for 3D lung tumor reconstruction by CT images. The proposed method consists of three stages: lung segmentation, tumor segmentation and 3D lung tumor reconstruction. Lung and tumor segmentation are performed using snake optimization and Gustafson-Kessel (GK) clustering. In the 3D reconstruction part first, features are extracted using the pre-trained VGG model from the tumors that detected in 2D CT slices. Then, a sequence of extracted features is fed into an LSTM to output compressed features. Finally, the compressed feature is used as input for GAN, where the generator is responsible for high-level reconstructing the 3D image of the lung tumor. The main novelty of this paper is the use of GAN to reconstruct a 3D lung tumor model for the first time, to the best of our knowledge. Also, we used knowledge transfer to extract features from 2D images to speed up the training process. The results obtained from the proposed model on the LUNA dataset showed better results than state of the art. According to HD and ED metrics, the proposed method has the lowest values of 3.02 and 1.06, respectively, as compared to those of other methods. The experimental results show that the proposed method performs better than previous similar methods and it is useful to help practitioners in the treatment process.

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Section: Empirical Evaluationsmentioning

confidence: 99%

A GAN-based method for 3D lung tumor reconstruction boosted by a knowledge transfer approach

Rezaei

Ahmadi

2023

Multimed Tools Appl

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“…Cluster group keys are diverse from one cluster to another. Also in [23], an optical selective encryption scheme for the medical image based on the fast and robust fuzzy C-means clustering (FRFCM) algorithm and face biometric has been proposed.…”

Section: Related Workmentioning

confidence: 99%

A Real-Time Biometric Encryption Scheme Based on Fuzzy Logic for IoT

2022

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When milliards of smart devices are connected to the Internet using the Internet of Things (IoT), robust security methods are required to deliver current information to the objects. Using IoT, the user can be accessed via smart device applications at any time and any place, which challenges IoT security and privacy. From security point of view, users and smart devices should have secure communication channel and digital ID. Authentication is the first step towards any security action. Biometric-based authentication can ensure higher security for developing secure access. In this paper, fingerprint is used as the biometric factor. After scanning the fingerprint using the cellphone’s camera, the image is transmitted to the authentication system. Since the comparison time increases after increasing the database volume, instead of storing the scanned fingerprint image, some key features of the scanned fingerprint are extracted and transmitted to the learning system of the convolutional neural network for detection and authentication and stored in the database. In the user authentication phase, the authentication keys are identified and the passcodes for the user of interest are extracted, and zero code is sent to the forged people; finally, the passcode is examined to check if the user is legal or illegal. In this step, the legal codes for fuzzy encoding of the image and text information are activated, and encryption is carried out in multiple steps depending on the number of members. The final code is compressed using Huffman coding and used for transmission to the network or storage. The proposed method is tested in MATLAB, and the results show that an excellent security is achieved using this cascade encryption method. Conclusively, the proposed hybrid coding technique reduces the information volume by 15.9%.

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“…With the fast development and application of network technology, image information is more and more widely used in our daily life for different purposes such as medical images, scanned images, and remote sensing images Hossein Movafegh Ghadirli and Enayatifar [1]; Jianfeng Zhao et al [2]; Sui and Gao [3]; Nanrun Zhou et al [4]; Yuxin Shen et al [5]; Xiaoyong Ji et al [6]. To prevent image information from being attacked by hackers and other illegal elements during the network transmission process, which poses a threat to information security, researchers from various countries have studied various methods to hide and protect image information Gen Liu and Jiang [7]; Yuzhen Li et al [8]; Xingyuan Wang and Cao [9]; Wang and Sun [10]; Vidhya and Brindha [11].…”

Section: Introductionmentioning

confidence: 99%

Image encryption scheme based on a controlled zigzag transform and bit-level encryption under the quantum walk

Zhang

Wang²

2023

Front. Phys.

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With the rapid development of science and technology and network technology, the study of information security has become a hot spot, and image encryption has potential value in this regard. In this paper, an image encryption scheme based on controlled zigzag transform and bit-level encryption under the quantum walk environment is proposed. First, the parameters of the alternating quantum walk are obtained using the SHA-256 method, and the probability matrix of the quantum distribution on the two-dimensional lattice is obtained by multiple walk measurements; second, the spatial dislocation and bit-level dislocation of the image are realized by performing controlled zigzag dislocation and three-dimensional tesseract-like rotational dislocation on the color image; finally, after preprocessing the probability matrix of the quantum distribution, the matrix is bitwise with the dislocated image to achieve the encryption protection of image information. The effectiveness of the encryption scheme is verified by simulation experiments, and the scheme has a significant encryption effect. Compared with other encryption schemes, this scheme has better key sensitivity and dislocation effect, which provides a new approach to the field of image quantum encryption.

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Optical selective encryption based on the FRFCM algorithm and face biometric for the medical image

Cited by 33 publications

References 32 publications

A GAN-based method for 3D lung tumor reconstruction boosted by a knowledge transfer approach

A GAN-based method for 3D lung tumor reconstruction boosted by a knowledge transfer approach

A Real-Time Biometric Encryption Scheme Based on Fuzzy Logic for IoT

Image encryption scheme based on a controlled zigzag transform and bit-level encryption under the quantum walk

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