Weixin Bian

Anhui Normal University | AHNU · school of computer and information

The identification of low-resolution fingerprints has always been one of the focuses in the field of biometric identification. This paper proposes a method for super-resolving low-resolution fingerprints based on deep dictionary learning. First, it is necessary to obtain a priori based on the fingerprint ridge orientation. After obtaining it, the r...

The method of image super-resolution reconstruction through the dictionary usually only uses a single-layer dictionary, which not only cannot extract the deep features of the image but also requires a large trained dictionary if the reconstruction effect is to be better. This paper proposes a new deep dictionary learning model. Firstly, after prepr...

In a mobile edge computing environment, the computing tasks of resource-constrained IoT devices are often offloaded to mobile edge computing servers for processing. In order to ensure the security of the task offloading process, both parties need to perform mutual authentication and negotiate a session key first. The security defenses in the existi...

The method of image super-resolution reconstruction through a dictionary usually only uses a single-layer dictionary, which not only fails to extract the deep features of the image, but also the trained dictionary may be relatively large. This paper proposes a new deep dictionary learning model. First, after preprocessing the images of the training...

With the development of wireless communication technology and the rapid increase of user data, multi-server key agreement authentication scheme has been widely used. In order to protect users’ privacy and legitimate rights, a two-factor multi-server authentication scheme based on device PUF and users’ biometrics is proposed. The users’ biometrics a...

Dynamic functional connectivity (dFC) networks derived from resting-state functional magnetic resonance imaging (rs-fMRI) help us understand fundamental dynamic characteristics of human brains, thereby providing an efficient solution for automated identification of brain diseases, such as Alzheimer's disease (AD) and its prodromal stage. Existing s...

We propose an efficient identity authentication protocol based on cancelable biometric and Physical Uncloable Function (PUF) namely BioF-TAP, which realizes the two-way authentication between the user and the server. Specially, the concept of biometric template protection is added to the proposed protocol to better protect user privacy. We use the...

With the development of Internet technology and the change of network environment, it is particularly important to ensure the security and privacy of biometrics in the process of biometrics authentication. In this regard, we propose a novel identity authentication protocol based on cancelable biometric and Physical Unclonable Function (PUF) which u...

In mobile edge computing, the computing tasks of IoT terminal devices with limited computing power often need to be offloaded to servers for processing. However, there are malicious attacks by adversaries and malicious behaviors of servers in the network, coupled with the use of insecure network channels for data information transmission. These fac...

One of the most common solutions for the prevention of fire accidents is to conduct extensive fire evacuation drills in crowded places. However, there are multiple salient advantages to using virtual reality technology to simulate emergency solutions, for instance, saving costs and greatly decreasing uncertain risks or accidents. Therefore, in this...

Functional connectivity networks (FCNs) based on the resting-state functional magnetic imaging (rs-fMRI) can help to enhance our knowledge and understanding of brain function, and have been applied to diagnosis of brain diseases, such as Alzheimer’s disease (AD) and its prodromal stage, i.e., mild cognitive impairment (MCI). Traditional methods usu...

Dynamic functional connectivity (dFC) networks based on resting-state functional magnetic resonance imaging (rs-fMRI) can help us understand the function of brain better, and have been applied to brain disease identification, such as Alzheimer’s disease (AD) and its early stages (i.e., mild cognitive impairment, MCI). Deep learning (e.g., convoluti...

Functional connectivity (FC) networks derived from resting-state functional magnetic resonance imaging (rs-fMRI) have been widely used in automated identification of brain disorders, such as Alzheimer’s disease (AD) and attention deficit hyperactivity disorder (ADHD). To generate compact representations of FC networks, various thresholding methods...

Numerous data hiding algorithms have been devised for imperceptibly embedding secret messages into the cover media so as to securely transmit user privacy information over the public communication channels. Among them, the reference matrix-based schemes in spatial domain draw extensive concern on account of the simple but efficient embedding and ex...

With the current development and popularization of biometrics recognition technology, our biometrics and other identity information may be illegal bulk scalping, and there is the possibility of being used for false enrolment, network fraud and other illegal criminal activities. Although some network platforms based on biometrics recognition adopt m...

Region-based Convolutional Neural Network (R-CNN) detectors have achieved state-of-the-art results on various challenging benchmarks. Although R-CNN has achieved high detection performance, the research of local information in producing candidates is insufficient. In this paper, we design a Keypoint-based Faster R-CNN (K-Faster) method for object d...

In order to improve the quality of fingerprint with a large noise, this study proposes a fingerprint enhancement method by using a sparse representation of learned multi-scale classification dictionaries with reduced dimensionality. The multi-scale dictionary is used to balance the contradiction between the accuracy and the anti-noise ability, whic...

The emergence of multi-server authentication key protocol schemes provides a viable environment for users to easily access the services of multiple legitimate servers through a single registration. Biometric identification technology has the characteristics of forgery difficulty, duplication difficulty and guess difficulty, etc. Therefore, it is an...

With the rapid development of Web Virtual Reality (WebVR) technology, increasing focus has been placed on this domain.WebVR indoor scenario design studies have been of important value in both academia and industry. However, many bottlenecks still need to be overcome, such as the weak computing capacity and limited memory space available in web brow...

Functional connectivity (FC) networks based on functional magnetic resonance imaging (fMRI) data have been widely applied to automated identification of brain diseases, such as attention deficit hyperactivity disorder (ADHD) and Alzheimer’s disease (AD). To generate compact representations of FC networks for disease analysis, various thresholding s...

Feature selection has been applied to the analysis of complex structured data, such as functional connectivity networks (FCNs) constructed on resting-state functional magnetic resonance imaging (rs-fMRI), for removing redundant/noisy information. Previous studies usually first extract topological measures (e.g., clustering coefficients) from FCNs a...

Fingerprint orientation field (FOF) estimation plays a key role in enhancing the performance of automated fingerprint identification system (AFIS): accurate estimation of FOF can evidently improve the performance of AFIS. However, despite the enormous attention on the FOF estimation research in the past decades, accurate estimation of FOFs, especia...

Orientation pattern is an important feature for characterizing fingerprint and plays a very important role in the automatic fingerprint identification system (AFIS). Conventional gradient based methods are popular but very sensitive to noise. In this paper, we present an improved fingerprint orientation field (FOF) extraction method based on qualit...

Fingerprint enhancement plays a very important role in automatic fingerprint identification system (AFIS). In order to ensure reliable fingerprint identification and improve fingerprint ridge structure, a novel method based upon the collaborative filtering model for fingerprint enhancement is proposed. The proposed method consists of two stages. Fi...

2D adaptive Chebyshev band-pass filter (ACBF) with orientation-selective, a novel fingerprint enhancement filter, is designed in this paper. The fingerprint enhancement is deeply rooted in the spectra diffusion by performing the 2D ACBF with orientation-selective in the frequency domain. The process of the enhancement is to have two phases: fingerp...

This study presents a new method for enhancing fingerprint image. The process of the enhancement is divided into two phases: fingerprint is first enhanced using Gabor filtering and then the enhanced fingerprint can be further enhanced by using sparse representation with the priori information of ridge pattern based on classification dictionaries le...

This paper presents a novel algorithm for reconstructing the fingerprint orientation field (FOF). The basic idea of the algorithm is to reconstruct the FOF by combining weighted linear project analysis with orientation diffusion. We first compute the weight values of point gradients according to the similarity of point orientations. In the second p...

A new algorithm for reconstructing the fingerprint super-resolution (SR) image is presented. The basic idea of the algorithm is to reconstruct the SR image by using sparse representation with ridge pattern prior based on classification coupled dictionaries. First, the orientations of training patches are estimated by the weighted linear projection...

Outlier detection is an interesting issue in data mining and machine learning. In this paper, to detect outliers, an information-entropy-based k-nearest neighborhood relevant outlier factor algorithm is proposed that is combined with Shannon information theory and the triangle pruning strategy. The algorithm accounts for the data points whose k-nea...

To improve object recognition capabilities in applications, we used orthogonal design (OD) to choose a group of optimal parameters in the parameter space of scale invariant feature transform (SIFT). In the case of global optimization (GOP) and local optimization (LOP) objectives, our aim is to show the operation of OD on the SIFT method. The GOP ai...

This paper proposes a novel algorithm for reconstructing the fingerprint orientation field (FOF). The basic idea of the algorithm is to reconstruct the ridge orientation by using the best quadratic approximation by orthogonal polynomials in two discrete variables. We first estimate the local region orientation by the linear projection analysis (LPA...

Snake (Active Contour)Model, introduced by Kass in 1987, is a dynamic curve model with energy-minimizing. Snake algorithm, which has advantages in extracting target object from a certain region, is an effective method in image segmentation. Based on the analysis of the snake model and the regional information of the edges of the fingerprint images,...