Signal processing and machine learning techniques for human verification based on finger textures

PhD ThesisIn recent years, Finger Textures (FTs) have attracted considerable attention as potential biometric characteristics. They can provide robust recognition performance as they have various human-speci c features, such as wrinkles and apparent lines distributed along the inner surface of all ngers. The main topic of this thesis is verifying people according to their unique FT patterns by exploiting signal processing and machine learning techniques. A Robust Finger Segmentation (RFS) method is rst proposed to isolate nger images from a hand area. It is able to detect the ngers as objects from a hand image. An e cient adaptive nger segmentation method is also suggested to address the problem of alignment variations in the hand image called the Adaptive and Robust Finger Segmentation (ARFS) method. A new Multi-scale Sobel Angles Local Binary Pattern (MSALBP) feature extraction method is proposed which combines the Sobel direction angles with the Multi-Scale Local Binary Pattern (MSLBP). Moreover, an enhanced method called the Enhanced Local Line Binary Pattern (ELLBP) is designed to e ciently analyse the FT patterns. As a result, a powerful human veri cation scheme based on nger Feature Level Fusion with a Probabilistic Neural Network (FLFPNN) is proposed. A multi-object fusion method, termed the Finger Contribution Fusion Neural Network (FCFNN), combines the contribution scores of the nger objects. The veri cation performances are examined in the case of missing FT areas. Consequently, to overcome nger regions which are poorly imaged a method is suggested to salvage missing FT elements by exploiting the information embedded within the trained Probabilistic Neural Network (PNN). Finally, a novel method to produce a Receiver Operating Characteristic (ROC) curve from a PNN is suggested. Furthermore, additional development to this method is applied to generate the ROC graph from the FCFNN. Three databases are employed for evaluation: The Hong Kong Polytechnic University Contact-free 3D/2D (PolyU3D2D), Indian Institute of Technology (IIT) Delhi and Spectral 460nm (S460) from the CASIA Multi-Spectral (CASIAMS) databases. Comparative simulation studies con rm the e ciency of the proposed methods for human veri cation. The main advantage of both segmentation approaches, the RFS and ARFS, is that they can collect all the FT features. The best results have been benchmarked for the ELLBP feature extraction with the FCFNN, where the best Equal Error Rate (EER) values for the three databases PolyU3D2D, IIT Delhi and CASIAMS (S460) have been achieved 0.11%, 1.35% and 0%, respectively. The proposed salvage approach for the missing feature elements has the capability to enhance the veri cation performance for the FLFPNN. Moreover, ROC graphs have been successively established from the PNN and FCFNN.the ministry of higher education and scientific research in Iraq (MOHESR); the Technical college of Mosul; the Iraqi Cultural Attach e; the active people in the MOHESR, who strongly supported Iraqi students

Computer-Aided Design (CAD) Tools to Support the Human Factors Design Teams

The scope of this assessment was to develop a library of basic 1-Gravity (G) human posture and motion elements used to construct complex virtual simulations of ground processing and maintenance tasks for spaceflight vehicles, including launch vehicles, crewed spacecraft, robotic spacecraft, satellites, and other payloads. The report herein describes the task, its purpose, performance, findings, NASA Engineering and Safety Center (NESC) recommendations, and conclusions in the definition and assemblage of the postures and motions database (PMD)

Handbook of Vascular Biometrics

This open access handbook provides the first comprehensive overview of biometrics exploiting the shape of human blood vessels for biometric recognition, i.e. vascular biometrics, including finger vein recognition, hand/palm vein recognition, retina recognition, and sclera recognition. After an introductory chapter summarizing the state of the art in and availability of commercial systems and open datasets/open source software, individual chapters focus on specific aspects of one of the biometric modalities, including questions of usability, security, and privacy. The book features contributions from both academia and major industrial manufacturers

A Novel Convolutional Neural Network Pore-Based Fingerprint Recognition System

Biometrics play an important role in security measures, such as border control and online transactions, relying on traits like uniqueness and permanence. Among the different biometrics, the fingerprint stands out for their enduring nature and individual uniqueness. Fingerprint recognition systems traditionally rely on ridge patterns (Level 1) and minutiae (Level 2). However, these systems suffer from recognition accuracy with partial fingerprints. Level 3 features, such as pores, offer distinctive attributes crucial for individual identification, particularly with high-resolution acquisition devices. Moreover, the use of convolutional neural networks (CNNs) has significantly improved the accuracy in automatic feature extraction for biometric recognition. A CNN-based pore fingerprint recognition system consists of two main modules, pore detection and pore feature extraction and matching modules. The first module generates pixel intensity maps to determine the pore centroids, while the second module extracts relevant features of pores to generate pore representations for matching between query and template fingerprints. However, existing CNN architectures lack in generating deep-level discriminative feature and computational efficiency. Moreover, available knowledge on the pores has not been taken into consideration optimally for pore centroids and metrics other than Euclidean distance have not been explored for pore matching. The objective of this research is to develop a CNN-based pore fingerprint recognition scheme that is capable of providing a low-complexity and high-accuracy performance. The design of the CNN architecture of the two modules aimed at generating features at different hierarchical levels in residual frameworks and fusing them to produce comprehensive sets of discriminative features. Depthwise and depthwise separable convolution operations are judiciously used to keep the complexity of networks low. In the proposed pore centroid part, the knowledge of the variation of the pore characteristics is used. In the proposed pore matching scheme, a composite metric, encompassing the Euclidean distance, angle, and magnitudes difference between the vectors of pore representations, is proposed to measure the similarity between the pores in the query and template images. Extensive experiments are performed on fingerprint images from the benchmark PolyU High-Resolution-Fingerprint dataset to demonstrate the effectiveness of the various strategies developed and used in the proposed scheme for fingerprint recognition

IF YOU SUFFER FOR DOING GOOD: The Life and Work of Margaret Arach Orech of Uganda

In the following pages, you will find narrative stories about a Woman PeaceMaker, along with additional information to provide a deep understanding of a contemporary conflict and one person’s journey within it. These complementary components include a brief biography of the peacemaker, a historical summary of the conflict, a timeline integrating political developments in the country with personal history of the peacemaker, and a question-and-answer transcript of select interviews during her time at the Joan B. Kroc Institute for Peace and Justice. Margaret Arach Orech is the founder and director of the Uganda Landmine Survivors Association (ULSA). A survivor of a landmine explosion and a subsequent attack by rebels of the Lord’s Resistance Army (LRA), Orech is an ambassador for the Nobel Peace Prize- winning organization the International Campaign to Ban Landmines. In the late 1990s, while working for the Association of Volunteers in International Service, in Kitgum in northern Uganda, the bus she was riding in hit a landmine and was ambushed by the LRA. Her right leg was shattered from the blast; as the rebels scoured the bodies for survivors, she played dead until the army came nearly an hour later. Orech has worked since that time for the health and rights of fellow survivors of landmines and victims of the war in northern Uganda. Orech’s work with communities affected by the conflict in northern Uganda includes encouraging dialogue and interaction with other survivors of violence, including former rebels. In one case, she came face to face with a young man who was part of the group responsible for the attack that nearly killed her. Showing him compassion upon his expression of remorse, she helped organize a traditional cleansing ceremony to help him begin his slow journey to recovery. With ULSA, Orech mobilizes survivors in a peer support structure in which they share and develop ideas that address survivors’ needs and foster social and economic reintegration into their communities — many of which were displaced for years because of the violence in northern Uganda. On the international level, Orech is a commissioner for the Interfaith Action for Peace in Africa, and continues to lobby nations to sign and ratify international agreements such as the Mine Ban Treaty, the Convention on Cluster Munitions, and the U.N. Convention on the Rights of Persons with Disabilities. She has met with heads of state and those in the midst of conflict to advocate on behalf of victims and survivors. Of her experiences she writes, “My healing was a drawn [out] process, but I was able to overcome and now use the bitter experiences to encourage those who have faced similar situations that there is actually hope after all. ... Here I am, today, after that long and difficult road to recovery and the transformation from victim-survivor to peace advocate.”https://digital.sandiego.edu/ipj-research/1012/thumbnail.jp

Escaping Cascadia

The preface, Dualism and Narrative Mode, details the development of realist techniques and then looks to current research to address the question, In what other ways can realism be maximized within fiction? It proposes a style combining second-person imperative narration for the viewpoint character’s actions and third-person free indirect discourse for description and internalization. The introduction, The Geography of the Future, explores prediction within select literary works, explains mitigation reactions to such predictions, and details current geographical projections to build a picture of what the future will look like and how humans will interact with their environment. Escaping Cascadia is a novel written in the style proposed by the preface, with the intent to maximize psychological realism and reader immersion, and to minimize the voice of a narrator and the reader’s awareness of an author. The story takes place within a world informed by the geographical exploration in the introduction

Pedagogical relationships: A master-apprentice model in music teaching

The thesis entitled Pedagogical Relationships: A master-apprentice model in music teaching is a pedagogical and phenomenological inquiry into the lived experience of the master-apprentice model of piano teaching in a private studio. It surveys the history of the instrument, its literature, its pedagogy and the importance of genealogy in this mentor-protégé relationship. Using narratives, interviews, audio-visual links, illustrations, musical score illustrations and literary references, the thesis illuminates authentic lived experiences of both teacher and student