Thermal handprint analysis for forensic identification using Heat-Earth Mover's Distance

Abstract

In recent years, handprint-based recognition system has been widely applied in forensic science. However, existing identification systems are nearly based on the handprints that could be easily prevented. In contrast to earlier works, we exploit the thermal handprint dissimilarity measure, called Heat-Earth Mover's Distance (HEMD). It is designed to classify heat-based handprints that can be obtained even when the subject wears a glove.Our objective is to develop a system that performs a forensic identification using heat-based handprints 1. Thermal handprints made without the glove 2. Thermal handprint made with the glove Existing forensic identification systems:1. DNA fingerprinting (blood, skin, hair, saliva) uses a length of the strands of the DNA molecules with repeating base pair patterns by restricting fragment length polymorphism (RFLP) 2. Odor analysis uses a chemical analysis of perfume components by gas chromatography (GC) 3. Voice analysis using Gaussian mixture speaker models achieved an accuracy of 82.8% (Reynolds et al). 4. Fingerprint / handprint uses a minutiae-based structural matching. Previously, handprint-based verification system made by integrating hand geometry feature and fingerprint feature achieved an accuracy of 97% (Yan et al). when acceptance error and rejection error become equal. The lower the EER, the higher the accuracy. Relatively low EER of SH indicates that SH is more stable than using GH Figure 5. our task is to transport the points from the target X to training Y with the least cost. Second equation allows the overall weight of points in X to be equal to the overall weight of points in Y. Thus, weight normalization is not needed. Figure 2.Limitations: