State-of-the-Art: A Systematic Literature Review of Image Segmentation in Latent Fingerprint Forensics

Author(s): Megha Chhabra*, Manoj Kumar Shukla, Kiran Kumar Ravulakollu

Journal Name: Recent Advances in Computer Science and Communications
Formerly Recent Patents on Computer Science

Volume 13 , Issue 6 , 2020

Become EABM
Become Reviewer
Call for Editor

Graphical Abstract:


Latent fingerprints are unintentional finger skin impressions left as invisible ridge patterns at crime scenes or objects. A major challenge in latent fingerprint forensics is the poor quality of the lifted image from the crime scene captured by investigators. Forensics investigators are in permanent search of novel breakthroughs in effective technologies to capture and process such low-quality images. The accuracy of the recognition often depends upon 1) the quality of the image captured at the beginning, 2) metrics used to assess the quality and thereafter 3) the level of enhancement required. Low-performance scanners, unstructured background noise, poor ridge quality, overlapping structured noise, etc. are often reasoned for poor image quality. Insufficient image quality results in the detection of false minutiae and hence reduces the recognition rate. Traditionally, image segmentation and enhancement are manually carried out from highly skilled experts. The use of an automated system is definitely challenging and can only be effective, if a significant amount of time is saved. This survey amplifies a comparative study of various segmentation techniques available for latent fingerprint forensics.

Keywords: Latent fingerprint, image segmentation, feature selection, forensics science, crime scenes, finger skin impressions.

Rights & PermissionsPrintExport Cite as

Article Details

Year: 2020
Published on: 28 January, 2021
Page: [1115 - 1125]
Pages: 11
DOI: 10.2174/2213275912666190429153952
Price: $25

Article Metrics

PDF: 10