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Identifying images generated by Generative Adversarial Networks (GANs) has become a significant challenge in digital image forensics. This research presents a wavelet-based detection method that uses discrete wavelet transform (DWT)…

Biometric-based identification has drawn a lot of attention in the recent years. Among all biometrics, palmprint is known to possess a rich set of features. In this paper we have proposed to use DCT-based features in parallel with…

This paper present a novel off-line signature recognition method based on multi scale Fourier Descriptor and wavelet transform . The main steps of constructing a signature recognition system are discussed and experiments on real data sets…

Singular points of a fingerprint image are special locations having high curvature properties. They can play a pivotal role in fingerprint normalization and reliable feature extraction. Accurate and efficient extraction of a singular point…

Fingerphoto images captured using a smartphone are successfully used to verify the individuals that have enabled several applications. This work presents a novel algorithm for fingerphoto verification using a nested residual block:…

The objective of this work is to propose a novel methodology for the finger knuckle print recognition, which is essentially a digital photo of the finger-knuckle region. We have employed very simple concepts of visual computing such as a…

With the growing use of biometric authentication systems in the past years, spoof fingerprint detection has become increasingly important. In this work, we implement and evaluate two different feature extraction techniques for…

Signature verification is an authentication technique that considers handwritten signature as a biometric. From a biometric perspective this project made use of automatic means through an integration of intelligent algorithms to perform…

Even though a few initial works have shown on small sets of data some level of bias in the performance of fingerprint recognition technology with respect to certain demographic groups, there is still not sufficient evidence to understand…

Fingerprints are the most widely deployed form of biometric identification. No two individuals share the same fingerprint because they have unique biometric identifiers. This paper presents an efficient fingerprint verification algorithm…

Palmprint recognition has drawn a lot of attention during the recent years. Many algorithms have been proposed for palmprint recognition in the past, majority of them being based on features extracted from the transform domain. Many of…

A light-weight low-resolution face gender classification method, called FaceHop, is proposed in this research. We have witnessed rapid progress in face gender classification accuracy due to the adoption of deep learning (DL) technology.…

To improve diagnostic accuracy of breast cancer detection, several researchers have used the wavelet-based tools, which provide additional insight and information for aiding diagnostic decisions. The accuracy of such diagnoses, however, can…

This paper presents an effective method for fingerprint verification based on a data mining technique called minutiae clustering and a graph-theoretic approach to analyze the process of fingerprint comparison to give a feature space…

Finger vein recognition has drawn increasing attention as one of the most popular and promising biometrics due to its high distinguishes ability, security and non-invasive procedure. The main idea of traditional schemes is to directly…

Our research aims at classifying individuals based on their unique interactions on touchscreen-based smartphones. In this research, we use Touch-Analytics datasets, which include 41 subjects and 30 different behavioral features.…

This paper presents an effective method for fingerprint classification using data mining approach. Initially, it generates a numeric code sequence for each fingerprint image based on the ridge flow patterns. Then for each class, a seed is…

Smartphones consist of different sensors, which provide a platform for data acquisition in many scientific researches such as driving style identification systems. In the present paper, smartphone data are used to evaluate the driving…

Transformer models have shown impressive performance on a variety of NLP tasks. Off-the-shelf, pre-trained models can be fine-tuned for specific NLP classification tasks, reducing the need for large amounts of additional training data.…

In this paper, a new method for handwritten signature identification based on rotated complex wavelet filters is proposed. We have proposed to use the rotated complex wavelet filters (RCWF) and dual tree complex wavelet transform(DTCWT)…