Finger Vein Image Deblurring Using Neighbors-Based Binary-GAN (NB-GAN)

Vein contraction and venous compression typically caused by low temperature and excessive placement pressure can blur the captured finger vein images and severely impair the quality of extracted features. To improve the quality of captured finger vein image, this paper proposes a 26-layer generator network constrained by Neighbors-based Binary Patterns (NBP) texture loss to recover the clear image (guessing the original clear image). Firstly, by analyzing various types and degrees of blurred finger vein images captured in real application scenarios, a method to mathematically model the local and global blurriness using a pair of defocused and mean blur kernels is proposed. By iteratively and alternatively convoluting clear images with both kernels in a multi-scale window, a polymorphic blur training set is constructed for network training. Then, NBP texture loss is used for training the generator to enhance the deblurring ability of the network on images. Lastly, a novel network structure is proposed to retain more vein texture feature information, and two residual connections are added on both sides of the residual module of the 26-layer generator network to prevent degradation and overfitting. Theoretical analysis and simulation results show that the proposed neighbors-based binary-GAN (NB-GAN) can achieve better deblurring performance than the the-state-of-the-art approaches

Biometric Systems

Biometric authentication has been widely used for access control and security systems over the past few years. The purpose of this book is to provide the readers with life cycle of different biometric authentication systems from their design and development to qualification and final application. The major systems discussed in this book include fingerprint identification, face recognition, iris segmentation and classification, signature verification and other miscellaneous systems which describe management policies of biometrics, reliability measures, pressure based typing and signature verification, bio-chemical systems and behavioral characteristics. In summary, this book provides the students and the researchers with different approaches to develop biometric authentication systems and at the same time includes state-of-the-art approaches in their design and development. The approaches have been thoroughly tested on standard databases and in real world applications

Method for estimating potential recognition capacity of texture-based biometrics

When adopting an image-based biometric system, an important factor for consideration is its potential recognition capacity, since it not only defines the potential number of individuals likely to be identifiable, but also serves as a useful figure-of-merit for performance. Based on block transform coding commonly used for image compression, this study presents a method to enable coarse estimation of potential recognition capacity for texture-based biometrics. Essentially, each image block is treated as a constituent biometric component, and image texture contained in each block is binary coded to represent the corresponding texture class. The statistical variability among the binary values assigned to corresponding blocks is then exploited for estimation of potential recognition capacity. In particular, methodologies are proposed to determine appropriate image partition based on separation between texture classes and informativeness of an image block based on statistical randomness. By applying the proposed method to a commercial fingerprint system and a bespoke hand vein system, the potential recognition capacity is estimated to around 10^36 for a fingerprint area of 25  mm^2 which is in good agreement with the estimates reported, and around 10^15 for a hand vein area of 2268  mm^2 which has not been reported before

Photoacoustic Elastography and Next-generation Photoacoustic Tomography Techniques Towards Clinical Translation

Ultrasonically probing optical absorption, photoacoustic tomography (PAT) combines rich optical contrast with high ultrasonic resolution at depths beyond the optical diffusion limit. With consistent optical absorption contrast at different scales and highly scalable spatial resolution and penetration depth, PAT holds great promise as an important tool for both fundamental research and clinical application. Despite tremendous progress, PAT still encounters certain limitations that prevent it from becoming readily adopted in the clinical settings. This dissertation aims to advance both the technical development and application of PAT towards its clinical translation. The first part of this dissertation describes the development of photoacoustic elastography techniques, which complement PAT with the capability to image the elastic properties of biological tissue and detect pathological conditions associated with its alterations. First, I demonstrated vascular-elastic PAT (VE-PAT), capable of quantifying blood vessel compliance changes due to thrombosis and occlusions. Then, I developed photoacoustic elastography to noninvasively map the elasticity distribution in biological tissue. Third, I further enhanced its performance by combing conventional photoacoustic elastography with a stress sensor having known stress–strain behavior to achieve quantitative photoacoustic elastography (QPAE). QPAE can quantify the Young’s modulus of biological tissues on an absolute scale. The second part of this dissertation introduces technical improvements of photoacoustic microscopy (PAM). First, by employing near-infrared (NIR) light for illumination, a greater imaging depth and finer lateral resolution were achieved by near-infrared optical-resolution PAM (NIR-OR-PAM). In addition, NIR-OR-PAM was capable of imaging other tissue components, including lipid and melanin. Second, I upgraded a high-speed functional OR-PAM (HF-OR-PAM) system and applied it to image neurovascular coupling during epileptic seizure propagation in mouse brains in vivo with high spatio-temporal resolution. Last, I developed a single-cell metabolic PAM (SCM-PAM) system, which improves the current single-cell oxygen consumption rate (OCR) measurement throughput from ~30 cells over 15 minutes to ~3000 cells over 15 minutes. This throughput enhancement of two orders of magnitude achieves modeling of single-cell OCR distribution with a statistically meaningful cell count. SCM-PAM enables imaging of intratumoral metabolic heterogeneity with single-cell resolution. The third part of this dissertation introduces the application of linear-array-based PAT (LA-PAT) in label-free high-throughput imaging of melanoma circulating tumor cells (CTCs) in patients in vivo. Taking advantage of the strong optical absorption of melanin and the unique capability of PAT to image optical absorption, with 100% relative sensitivity, at depths with high ultrasonic spatial resolution, LA-PAT is inherently suitable for melanoma CTC imaging. First, with a center ultrasonic frequency of 21 MHz, the LA-PAT system was able to detect melanoma CTCs clusters and quantify their sizes based on the contrast-to-noise ratio (CNR). Second, I developed an LA-PAT system with a center ultrasonic frequency of 40 MHz and imaged melanoma CTCs in patients in vivo with a CNR greater than 12. We successfully imaged 16 melanoma patients and detected melanoma CTCs in 3 of them. Among the CTC-positive patients, 67% had disease progression despite systemic therapy. In contrast, only 23% of the CTC-negative patients showed disease progression. This study lays a solid foundation for translating CTC detection to bedside for clinical care and decision-making

A Method for Obtaining Electronic Voting Systems based Voter Confidentiality and Voting Accuracy

A Voting is common in our daily life, from electing president to electing committee. A complete electronic voting scheme suitable for all kinds of voting with safe guaranty where the voter?s privacy can be protected. Fingerprint system security have been investigated, including the use of fake fingerprints for masquerading identity, the problem of fingerprint alteration or obfuscation has received very little attention. Fingerprint image quality assessment software (e.g., NFIQ) cannot always detect altered fingerprints since the implicit image quality due to alteration may not change significantly. The main contributions of this Research are-1.Compiling case studies of incidents where individuals were found to have altered their fingerprints for circumventing AFIS.2.Identifying the damages of fingerprint alteration on the accuracy of a commercial fingerprint matcher.3.Classifying the alterations into three major categories and suggesting possible countermeasures.4.Developing a technique to automatically detect altered fingerprints based on analyzing orientation field and minutiae distribution.5.Evaluating the proposed technique and the NFIQ algorithm on a big database of altered fingerprints provided by a law enforcement agency. Experimental results show the feasibility of the proposed approach in detecting altered fingerprints and highlight the need to further pursue this problem

Gait Verification using Knee Acceleration Signals

A novel gait recognition method for biometric applications is proposed. The approach has the following distinct features. First, gait patterns are determined via knee acceleration signals, circumventing difficulties associated with conventional vision-based gait recognition methods. Second, an automatic procedure to extract gait features from acceleration signals is developed that employs a multiple-template classification method. Consequently, the proposed approach can adjust the sensitivity and specificity of the gait recognition system with great flexibility. Experimental results from 35 subjects demonstrate the potential of the approach for successful recognition. By setting sensitivity to be 0.95 and 0.90, the resulting specificity ranges from 1 to 0.783 and 1.00 to 0.945, respectively

Carpal tunnel syndrome due to an atypical deep soft tissue leiomyoma: The risk of misdiagnosis and mismanagement

<p>Abstract</p> <p>Background</p> <p>Leiomyomas of the deep soft tissue are quite uncommon and occur even more rarely in upper extremity.</p> <p>Case presentation</p> <p>A 32-year old manual laborer man presented with a two-year history of numbness, tingling and burning pain in the palmar surface of the left hand and fingers. His medical history was unremarkable and no trauma episode was reported. According to the clinical examination and the result of median nerve conduction study (NCS) the diagnosis of carpal tunnel syndrome was established. Operative release of the transverse carpal ligament was subsequently performed but the patient experienced only temporary relief of his symptoms. MRI examination revealed a deep palmary located mass with well-defined margins and ovoid shape. Intraoperatively, the tumor was in continuity with the flexor digitorum superficialis tendon of the middle finger causing substantial compression to median nerve. Histopathological findings of the resected mass were consistent with leiomyoma. After two years the patient was pain-free without signs of tumor recurrence.</p> <p>Conclusion</p> <p>Despite the fact that reports on deep soft tissue leiomyoma are exceptional, this tumor had to be considered as differential diagnosis in painful non-traumatic hand syndromes especially in young patients.</p

Biometric Systems

Because of the accelerating progress in biometrics research and the latest nation-state threats to security, this book's publication is not only timely but also much needed. This volume contains seventeen peer-reviewed chapters reporting the state of the art in biometrics research: security issues, signature verification, fingerprint identification, wrist vascular biometrics, ear detection, face detection and identification (including a new survey of face recognition), person re-identification, electrocardiogram (ECT) recognition, and several multi-modal systems. This book will be a valuable resource for graduate students, engineers, and researchers interested in understanding and investigating this important field of study

Integration of biometrics and steganography: A comprehensive review

The use of an individual’s biometric characteristics to advance authentication and verification technology beyond the current dependence on passwords has been the subject of extensive research for some time. Since such physical characteristics cannot be hidden from the public eye, the security of digitised biometric data becomes paramount to avoid the risk of substitution or replay attacks. Biometric systems have readily embraced cryptography to encrypt the data extracted from the scanning of anatomical features. Significant amounts of research have also gone into the integration of biometrics with steganography to add a layer to the defence-in-depth security model, and this has the potential to augment both access control parameters and the secure transmission of sensitive biometric data. However, despite these efforts, the amalgamation of biometric and steganographic methods has failed to transition from the research lab into real-world applications. In light of this review of both academic and industry literature, we suggest that future research should focus on identifying an acceptable level steganographic embedding for biometric applications, securing exchange of steganography keys, identifying and address legal implications, and developing industry standards