Advancements and Challenges in Low-Quality Fingerprint Identification: A Comprehensive Survey

Abstract

Low-quality fingerprint identification has played a significant role in the field of biometric identification. Especially for those who are experts in the use of sophisticated biometric technology in jail security and criminal identification in recent years. Many factors affect the accuracy of low-quality fingerprint identification, such as the quality of the fingerprint image, the accusation device, the extraction tools, etc. Many approaches have been proposed in this field to improve low-quality fingerprint identification. In this paper, we discuss the main factors of the low-quality fingerprint, the main approach of the human biometric data, as well as the main factors of the low-quality of the fingerprint data. Also, we list the state of the art, most recent machine learning and deep learning approaches that have been used recently in this field. As the end, this field of research is still in progress to improve the quality of the identification progress