SUT-Lips-DB - A database of lips traces

Citation Author(s):
Dariusz Mrozek, Ewa Ostałowska, Bożena Małysiak-Mrozek
Submitted by:
Dariusz Mrozek
Last updated:
Sat, 06/16/2018 - 23:18
DOI:
10.21227/H2R04P
Data Format:
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License:
Creative Commons Attribution
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Abstract 

A database of lips traces
Cheiloscopy is a forensic investigation technique that deals with identification of humans based on lips traces. Lip prints are unique and permanent for each individual, and next to the fingerprinting, dental identification, and DNA analysis can be one of the basis for criminal/forensics analysis.

Here we make available SUT-Lips-DB database. SUT-Lips-DB is a database of lips traces collected from individuals representing males and females in different age. The database can be used to conduct further research related to image analysis in order to find characteristic traces and various types of classifications of individuals on the basis of characteristic features. The database is available for broader community of users.

Instructions: 

SUT-Lips-DB database is free for scientific and testing purposes. However, you are asked to cite the data set and our papers mentioned at Home Project web site every time when you publish your own research conducted with the use of our data set or when you compare your own results with ours.

The main ZIP archive contains several folders. Each folder may contain several lip traces as JPG files only for one person. Data are anonimized. The name of the folder contains the informormation on the gender of the person. Additional CSV file contains information about year of birth of people for who we collected samples.

Comments

Need dataset for biometrics project

Submitted by Wardah Farrukh on Tue, 05/07/2019 - 15:49

I am in need of this dataset for biometric project sir

Submitted by SUJITHRA KANMANI on Wed, 12/02/2020 - 02:12

We need this dataset for biometric project,thank you.

Submitted by Chen Yu on Wed, 10/06/2021 - 09:33

I need the dataset too.

Submitted by kaushik Roy on Tue, 11/02/2021 - 11:15

Dataset Files

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