Link to Pubmed [PMID] – 31999558
Link to DOI – 10.1016/j.compbiomed.2019.103475
Comput Biol Med 2020 Jan; 116(): 103475
The abnormal aging mechanism associated with drug abuse results in poor performance of face recognition systems on illicit drug addicts (mainly methamphetamine). Consequently, the high correlation between drug addiction and crime exaggerates the urge for further investigations to originate and overcome this problem. Concurrently, face asymmetry was found to play a significant role in face recognition and age estimation. Therefore, facial asymmetry assessment for meth-addicts is highly serviceable, acknowledging how meth addiction accelerates biological aging and causes severe face distortion. In this work, we address facial asymmetry for meth-addicts compared with ordinary people. We assess facial asymmetry by employing the most credible state-of-the-art tools for local and global two-dimensional (2D) methods. More specifically, we use a classical bilateral-based metric for local analysis, combined with a proposed global approach, that we refer to as the Area Mismatch metric, to give a vivid overview of geometrical facial asymmetry. Finally, we construct a metric for textural facial asymmetry assessment by employing the Structural Similarity Index (SSIM) for dual regions in a given face. We apply the aforementioned metrics on two databases, a recently collected meth-addicted database and a regular aging database (FERET). Statistical analysis indicated a significant increment of facial asymmetry for meth addicts while aging, three to five times more than ordinary people. This study definitively answers the question regarding the correlation between meth abuse and addiction and the increase of facial asymmetry. Also, it confirms previous findings concerning aging and increased facial asymmetry.