相关论文: Topological Invariant-Based Iris Identification vi…
Cross-spectral iris recognition is emerging as a promising biometric approach to authenticating the identity of individuals. However, matching iris images acquired at different spectral bands shows significant performance degradation when…
In the last few years, face morphing has been shown to be a complex challenge for Face Recognition Systems (FRS). Thus, the evaluation of other biometric modalities such as fingerprint, iris, and others must be explored and evaluated to…
Topological features such as persistence diagrams and their functional approximations like persistence images (PIs) have been showing substantial promise for machine learning and computer vision applications. This is greatly attributed to…
Even though face recognition in frontal view and normal lighting condition works very well, the performance degenerates sharply in extreme conditions. Recently there are many work dealing with pose and illumination problems, respectively.…
Intrusion detection system (IDS) plays an essential role in computer networks protecting computing resources and data from outside attacks. Recent IDS faces challenges improving flexibility and efficiency of the IDS for unexpected and…
Despite the significant advances in iris segmentation, accomplishing accurate iris segmentation in non-cooperative environment remains a grand challenge. In this paper, we present a deep learning framework, referred to as Iris R-CNN, to…
Biometrics systems have significantly improved person identification and authentication, playing an important role in personal, national, and global security. However, these systems might be deceived (or "spoofed") and, despite the recent…
Segmenting curvilinear structures in medical images is essential for analyzing morphological patterns in clinical applications. Integrating topological properties, such as connectivity, improves segmentation accuracy and consistency.…
Inferring topological and geometrical information from data can offer an alternative perspective on machine learning problems. Methods from topological data analysis, e.g., persistent homology, enable us to obtain such information,…
Iris recognition systems are a mature technology that is widely used throughout the world. In identification (as opposed to verification) mode, an iris to be recognized is typically matched against all N enrolled irises. This is the classic…
This paper discusses some topics related to the latest trends in the field of evolutionary approaches to iris recognition. It presents the results of an exploratory experimental simulation whose goal was to analyze the possibility of…
Iris recognition is widely used in high-security scenarios due to its stability and distinctiveness. However, iris images captured by different devices exhibit certain and device-related consistent differences, which has a greater impact on…
Post-mortem iris recognition is an emerging application of iris-based human identification in a forensic setup. One factor that may be useful in conditioning iris recognition methods is the tissue decomposition level, which is correlated…
The use of biometrics to authenticate users and control access to secure areas has become extremely popular in recent years, and biometric access control systems are frequently used by both governments and private corporations. However,…
Human Identity verification has always been an eye-catching goal in digital based security system. Authentication or identification systems developed using human characteristics such as face, finger print, hand geometry, iris, and voice are…
This study presents the first automated classifier designed to determine whether a pair of iris images originates from monozygotic individuals, addressing a previously untackled problem in biometric recognition. In Daugman-style iris…
Topological correctness plays a critical role in many image segmentation tasks, yet most networks are trained using pixel-wise loss functions, such as Dice, neglecting topological accuracy. Existing topology-aware methods often lack robust…
Topological structures in image data, such as connected components and loops, play a crucial role in understanding image content (e.g., biomedical objects). % Despite remarkable successes of numerous image processing methods that rely on…
Topological data analysis (TDA) is a relatively new field that is gaining rapid adoption due to its robustness and ability to effectively describe complex datasets by quantifying geometric information. In imaging contexts, TDA typically…
In this paper, we present a texture aware lightweight deep learning framework for iris recognition. Our contributions are primarily three fold. Firstly, to address the dearth of labelled iris data, we propose a reconstruction loss guided…