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In this paper, we have developed Biometric recognition system adopting hand based modality Handvein, which has the unique pattern for each individual and it is impossible to counterfeit and fabricate as it is an internal feature. We have…

Most finger vein feature extraction algorithms achieve satisfactory performance due to their texture representation abilities, despite simultaneously ignoring the intensity distribution that is formed by the finger tissue, and in some…

The amount and quality of datasets and tools available in the research field of hand pose and shape estimation act as evidence to the significant progress that has been made.However, even the datasets of the highest quality, reported to…

Current finger-vein or palm-vein recognition systems usually require direct contact of the subject with the apparatus. This can be problematic in environments where hygiene is of primary importance. In this work we present a contactless…

Biometric verification systems are deployed in various security-based access-control applications that require user-friendly and reliable person verification. Among the different biometric characteristics, fingervein biometrics have been…

Biometrics authentication is an effective method for automatically recognizing individuals. The authentication consists of an enrollment phase and an identification or verification phase. In the stages of enrollment known (training) samples…

In the medical domain, different computer-aided diagnosis systems have been proposed to extract blood vessels from retinal fundus images for the clinical treatment of vascular diseases. Accurate extraction of blood vessels from the fundus…

With the improvement of arithmetic power and algorithm accuracy of personal devices, biological features are increasingly widely used in personal identification, and palm vein recognition has rich extractable features and has been widely…

Finger vein biometrics is an approach to identifying individuals based on the unique patterns of blood vessels in their fingers, and the technology is advanced in image capture and processing techniques, which is leading to more efficient,…

Objects for detection usually have distinct characteristics in different sub-regions and different aspect ratios. However, in prevalent two-stage object detection methods, Region-of-Interest (RoI) features are extracted by RoI pooling with…

Despite the high biometric performance, finger-vein recognition systems are vulnerable to presentation attacks (aka., spoofing attacks). In this paper, we present a new and robust approach for detecting presentation attacks on finger-vein…

3D hand-object interaction data is scarce due to the hardware constraints in scaling up the data collection process. In this paper, we propose HOIDiffusion for generating realistic and diverse 3D hand-object interaction data. Our model is a…

The success of Deep Convolutional Neural Networks (CNNs) in recent years in almost all the Computer Vision tasks on one hand, and the popularity of low-cost consumer depth cameras on the other, has made Hand Pose Estimation a hot topic in…

The current interacting hand (IH) datasets are relatively simplistic in terms of background and texture, with hand joints being annotated by a machine annotator, which may result in inaccuracies, and the diversity of pose distribution is…

Local feature descriptors exhibit great superiority in finger vein recognition due to their stability and robustness against local changes in images. However, most of these are methods use general-purpose descriptors that do not consider…

Despite the growing adoption of electronic health records, many processes still rely on paper documents, reflecting the heterogeneous real-world conditions in which healthcare is delivered. The manual transcription process is time-consuming…

We present a fully automatic, graph-based technique for extracting the retinal vascular topology -- that is, how different vessels are connected to each other -- given a single color fundus image. Determining this connectivity is very…

DeepPrior is a simple approach based on Deep Learning that predicts the joint 3D locations of a hand given a depth map. Since its publication early 2015, it has been outperformed by several impressive works. Here we show that with simple…

Assessing the forensic value of hand images involves the use of unique features and patterns present in an individual's hand. The human hand has distinct characteristics, such as the pattern of veins, fingerprints, and the geometry of the…

Hand detection is essential for many hand related tasks, e.g. parsing hand pose, understanding gesture, which are extremely useful for robotics and human-computer interaction. However, hand detection in uncontrolled environments is…