Biometric is the science that deals with identification of individuals based on a person’s physical and behavioral attributes.

It is the most advanced technology used in modern world for identification of an individual via fingerprints, DNA, or iris.

Basic perspective of biometric authentication is that every person can be accurately identified by his or her physical or behavioral traits.

Biometric systems make use of fingerprint, hand geometry, iris, retina, face, hand-vein, facial thermograms, signature, or voice print to verify a person.

Quality of a biometric system is affected by two factors;

• Authenticity of a sensor used
• Degree of freedom offered by features extracted from sensed signals

Advancement of biometrics in various fields of forensic such as Fingerprint, DNA, Face, Palm prints, Iris, Voice, Odor and Gait Biometrics, is replacing manual methods of identification and analysis and also aids in a less time-consuming method for analysis whereas manual methods are slow and take more time to solve a crime.

Biometric system includes 3 major steps:

1. Feature Extraction
2. Feature Robustness
3. Feature Matching

How Does Biometrics Work?

Biometrics is solely an automated system to establish the identity of a person based on various physical and behavioral attributes of an individual.

It acquires these attributes and when at the time of the crime or establishing an identity of an individual, it extracts salient feature set from the data and helps to compare acquired feature set from a crime scene to that of a stored feature set in database.

This procedure helps in real-time identification of an individual with a database of a complete set of information, and hence provide a forensic scientist with a proper result of comparison.

Components of Biometric System

Sensor Setup

This device acquires all types of raw biometric features of a particular attribute and quality is increased by using scanning and camera device, and collected information is stored in the database.

Feature Extraction

Further, after assessing the quality of raw data, a template is formed by subjecting raw data to ‘signal enhancement algorithm’ to improve its quality and then this data is processed and set of traits are extracted to represent the unique features, this is stored in a database and known as a template.

Matching Module

In this module, templates found or recovered are compared with stored templates, and matching score between two is given, and based on the matching score identity of a person is established.

System Database

This database is a storage system of biometrics,  templates extracted from raw data along with some biographic information of the person is stored here permanently.

Biometric Identification And Verification

Applications of Biometrics in Forensic Investigations

The first application of biometrics was the Automated Fingerprint Identification System implemented in 1960, then in 1980s DNA profiling came into play and gradually the development of CCTVs, mobile phone and other electronics which introduced face, iris, fingerprint recognition became an important part of a biometric tool.

Fingerprint Biometrics

A fingerprint forms from the pattern of ridges and valleys on surface of a fingertip, the fingerprint technician scans the prints at the crime scene and algorithms of biometric system, marks all the minute characteristics in the print and then they are matched in the stored fingerprint database. IAFIS and AFIS are two such systems that aid in criminal investigation and response in real-time.

DNA Biometrics

Deoxyribose nucleic acid is the most vital and at same time common evidence found at the crime scene which can be extracted from ’n’ number of bodily materials, such as hair, teeth pulp, bone, mucus, semen, and blood.

DNA biometrics uses genetic profiling also known as genetic fingerprinting, in this process following steps are taken:

1. DNA is extracted from the sample.
2. DNA is segmented into VNTRs.
3. These VNTRs are compared with stored database.
CODIS - Combined DNA Index System, this system is launched by FBI IN 1990, which is used to identify suspects by matching DNA profiles, CODIS is assisting laboratories at all level to solve crimes.

Iris Biometrics

Different iris patterns unique to individuals are made into digital templates and then compared against stored templates.

The UK government started the iris program which enables travelers to enter a country via several British airports using only automatic iris recognition for identification.

Voice Biometrics

Identification of speaker from unique characteristics of his/her voice gave rise to voice biometrics, there are various tools such as AGNITIO’s Voice ID technology designed for police to perform speaker identification, also ‘VoiceGrid Nation’ this is a system that contains advance algorithms to match voices.

These tools allow building a huge database of known criminals or persons on  watch list so that it can take less time to identify the speaker and this technique has already been deployed in Mexico.

Biometric Technologies in Crime Detection

Techniques of biometrics overcome the limitations of delay in solving cases due to the cognitive abilities of humans or due to insufficient material for analysis, it increases the efficiency and accuracy of investigation.

Huge bulk of data can be processed and analyzed using digital algorithms and a scientific basis which is humanly impossible.

The multimodal biometric system is more reliable in crime detection as it involves two biometric pieces of evidence to enhance the result.

References

Saini, Monika, and Anup Kumar Kapoor. "Biometrics in Forensic Identification: Applications and Challenges." Journal of Forensic Medicine 1.2 (2016): n. pag. Print.

Jain, Anil K., and Arun Ross. "Bridging the Gap: From Biometrics to Forensics." Philosophical Transactions of the Royal Society B: Biological Sciences 370.1674 (2015): 20140254. Print.

Bowyer, Kevin W., Karen Hollingsworth, and Patrick J. Flynn. "Image Understanding for Iris Biometrics: A Survey." Computer Vision and Image Understanding 110.2 (2008): 281-307. Print.

Rattani, A., D. R. Kisku, M. Bicego, and M. Tistarelli. "Feature Level Fusion of Face and Fingerprint Biometrics." 2007 First IEEE International Conference on Biometrics: Theory, Applications, and Systems (2007): n. pag. Print.