Sharif Digital Repository

Among all biometric approaches, gait analysis is one of the most practical methods for human identity recognition. Gait has a lot of advantages over other biometrics like face recognition, iris recognition, fingerprint, etc. First and foremost, the gait data can be collected from a distance, and there is no need for subject’s cooperation. Another advantage of this biometric method is its cost-effectiveness and the fact that it does not need high-resolution images. But there are significant challenges in detecting and analyzing this feature. One of the most important challenges is decreased recognition accuracy caused by identity-irrelevant factors like camera viewpoint and changes in walking... 

The person identification by Electroencephalographic (EEG) signals has attracted the researchers’ great attention in recent years and lots of investigations have been developed. An identification system seeks to identify a person in a database. The advantage of using EEG signals for person identification is the difficulty in generating artificial signals for imposters. But more works need to be done to use EEG based biometric in real-life and this thesis is one of them. In this project we classify the EEG signals for person identification using AdaBoost algorithm. Adaptive boosting (AdaBoost) is a machine learning technique for pattern classification in which the performance of the weak... 

Biometric identification systems have become key components in data security and protecting sensitive information. Biometric methods, such as fingerprint recognition, have replaced traditional authentication methods due to their high security and efficiency. However, challenges like the potential to forge have highlighted the need for the development of more robust methods. A new approach in this field is the use of electroencephalography signals for identity verification, which not only provides high security but can also enhance the safety of brain-computer interfaces In this study, we introduce a cueless imagined speech paradigm based on natural word selection, where users select and... 

Frequently using Personal Identification Information has escalated the security concerns of bank accounts, emails, daily transactions, and other activities. Therefore, user access to such apps must be controlled. Traditional personal verification methods offer limited security because they might need to be remembered or stolen. Therefore, Biometric authentication, which identifies persons by their unique biological information, is gaining popularity. However, palm vein identification is highly secure because the vein patterns are not duplicated in other people, even in monozygotic twins. Moreover, it has a liveness detection and is convenient since the vein pattern cannot be faked,... 

Gait recognition is a biometric method that aims to extract an individual's walking patterns and identify their identities. This recognition method has gained significant attention due to its ability to operate over long distances without requiring direct interaction. Additionally, these extracted walking patterns can be beneficial in the healthcare field, particularly for early diagnosis of certain diseases. With the advancement of deep neural networks, remarkable progress has been achieved in this area. However, numerous challenges remain, including variations in clothing, occlusions, and recognition in practical scenarios. For recognition models to make accurate decisions in real-world...