Automated Region Masking Of Latent Overlapped Fingerprints

TL;DR

This paper introduces a fully automated algorithm for region masking of overlapped latent fingerprints, utilizing image processing techniques to improve efficiency and accuracy in fingerprint separation at crime scenes.

Contribution

The paper presents a novel automated method using blurring, erosion, and dilation for region masking of overlapped fingerprints, reducing manual effort and time.

Findings

Algorithm effectively automates region masking process

Visual results demonstrate improved accuracy

Reduces manual intervention in fingerprint separation

Abstract

Fingerprints have grown to be the most robust and efficient means of biometric identification. Latent fingerprints are commonly found at crime scenes. They are also of the overlapped kind making it harder for identification and thus the separation of overlapped fingerprints has been a conundrum to surpass. The usage of dedicated software has resulted in a manual approach to region masking of the two given overlapped fingerprints. The region masks are then further used to separate the fingerprints. This requires the user's physical concentration to acquire the separate region masks, which are found to be time-consuming. This paper proposes a novel algorithm that is fully automated in its approach to region masking the overlapped fingerprint image. The algorithm recognizes a unique approach of using blurring, erosion, and dilation in order to attain the desired automated region masks. The experiments conducted visually demonstrate the effectiveness of the algorithm.