The LUTBIO multimodal biometric database includes the following key features: - The database comprises nine types of biometric data: voice, face, finger, palm_touch, ECG, opisthenar, ear, palm_touchless, and periocular. - The database includes information on 306 subjects, with a balanced gender ratio of 162 males and 143 females. The age distribution is wide-ranging, from the youngest at 8 years old to the oldest at 90 years old. - The volunteers for the database come from naturally occurring human settlements, representing a large-scale statistical population. The collected biometric data reflects various changes in real-world environments. - The LUTBIO database provides both palm print (contact-based and contactless) and fingerprint (optical photos and scans) biometric information, aiming to promote the development of multimodal biometric authentication technologies and guide the creation of future multimodal biometric databases. - The biometric data in the LUTBIO database is highly decoupled, meaning that these data can be separated and independently processed without losing their original information. This provides flexibility for analyzing and improving single or multimodal recognition technologies, while also allowing researchers to optimize or recombine different biometric features for specific application scenarios.

✅✅✅Given that the paper has not yet been published, we have decided to upload sample data from 6 individuals first. Once the paper is published, we will release the entire dataset.

🥸🥸🥸Please read the collection protocol of the LUTBIO data set carefully, which is very important to us. Thank you.

The LUTBIO database provides a comprehensive resource for research in multimodal biometric authentication, featuring the following key aspects:

• Extensive Biometric Modalities: The database contains data from nine biometric modalities: voice, face, fingerprint, contact-based palmprint, electrocardiogram (ECG), opisthenar (back of hand), ear, contactless palmprint, and periocular region.

• Diverse Demographics: Data were collected from 306 individuals, with a balanced gender distribution of 164 males and 142 females, spanning an age range of 8 to 90 years. This diverse age representation enables analyses across a wide demographic spectrum.

• Representative Population Sampling: Volunteers were recruited from naturally occurring communities, ensuring a large-scale, statistically representative population. The collected data encompass variations observed in real-world environments.

• Support for Multimodal and Cross-Modality Research: LUTBIO provides both contact-based and contactless palmprint data, as well as fingerprint data (from optical images and scans), promoting advancements in multimodal biometric authentication. This resource is designed to guide the development of future multimodal databases.

• Flexible, Decouplable Data: The biometric data in the LUTBIO database are designed to be highly decouplable, enabling independent processing of each modality without loss of information. This flexibility supports both single-modality and multimodal analysis, empowering researchers to optimize, combine, and customize biometric features for specific applications.

✅ Data Availability: If you wish to use the LUTBIO dataset, please download the attached Word document, fill in the information, and send it as an attachment to rykeryang AT 163.com. We will process your request as soon as possible!

🥸 Important Notice: Please read the data collection protocol of the LUTBIO dataset carefully before use, as it is essential for understanding and correctly interpreting the dataset. Thank you.

😎 Good news! Our paper has been accepted by Information Fusion, and the DOI is https://doi.org/10.1016/j.inffus.2025.102945. We appreciate the reviewers and the editor for their efforts.🥰🥰🥰

The LUTBIO database provides a comprehensive resource for research in multimodal biometric authentication, featuring the following key aspects:

• Extensive Biometric Modalities: The database contains data from nine biometric modalities: voice, face, fingerprint, contact-based palmprint, electrocardiogram (ECG), opisthenar (back of hand), ear, contactless palmprint, and periocular region.

• Diverse Demographics: Data were collected from 306 individuals, with a balanced gender distribution of 164 males and 142 females, spanning an age range of 8 to 90 years. This diverse age representation enables analyses across a wide demographic spectrum.

• Representative Population Sampling: Volunteers were recruited from naturally occurring communities, ensuring a large-scale, statistically representative population. The collected data encompass variations observed in real-world environments.

• Support for Multimodal and Cross-Modality Research: LUTBIO provides both contact-based and contactless palmprint data, as well as fingerprint data (from optical images and scans), promoting advancements in multimodal biometric authentication. This resource is designed to guide the development of future multimodal databases.

• Flexible, Decouplable Data: The biometric data in the LUTBIO database are designed to be highly decouplable, enabling independent processing of each modality without loss of information. This flexibility supports both single-modality and multimodal analysis, empowering researchers to optimize, combine, and customize biometric features for specific applications.

✅ Data Availability: To facilitate early access, we are initially releasing sample data from 6 individuals. Upon publication of the paper, the full dataset will be made available.

🥸 Important Notice: Please read the data collection protocol of the LUTBIO dataset carefully before use, as it is essential for understanding and correctly interpreting the dataset. Thank you.

😎 Good news! Our paper has received revision comments, and we are carefully making revisions based on the feedback. We appreciate the reviewers and the editor for their efforts.🥰🥰🥰

🤠 We conducted further research based on the LUTBIO database and proposed AuthFormer: An Adaptive Multimodal Biometric Authentication Framework for Secure and Flexible Identity Verification. The code is available at https://github.com/RykerYang/Authformer-LUTBIO.git. Our work is currently under review for an international conference, where we are dealing with a malicious reviewer. We are in the process of responding and appealing—wish us luck! 🍀🍀🍀