title: Fingerprint pattern restoration by digital image processing techniques.
abstract: Fingerprint evidence plays an important role in solving criminal problems. However, defective (lacking information needed for completeness) or contaminated (undesirable information included) fingerprint patterns make identifying and recognizing processes difficult. Unfortunately. this is the usual case. In the recognizing process (enhancement of patterns, or elimination of "false alarms" so that a fingerprint pattern can be searched in the Automated Fingerprint Identification System (AFIS)), chemical and physical techniques have been proposed to improve pattern legibility. In the identifying process, a fingerprint examiner can enhance contaminated (but not defective) fingerprint patterns under guidelines provided by the Scientific Working Group on Friction Ridge Analysis, Study and Technology (SWGFAST), the Scientific Working Group on Imaging Technology (SWGIT), and an AFIS working group within the National Institute of Justice. Recently, the image processing techniques have been successfully applied in forensic science. For example, we have applied image enhancement methods to improve the legibility of digital images such as fingerprints and vehicle plate numbers. In this paper, we propose a novel digital image restoration technique based on the AM (amplitude modulation)-FM (frequency modulation) reaction-diffusion method to restore defective or contaminated fingerprint patterns. This method shows its potential application to fingerprint pattern enhancement in the recognizing process (but not for the identifying process). Synthetic and real images are used to show the capability of the proposed method. The results of enhancing fingerprint patterns by the manual process and our method are evaluated and compared.
authors.affiliation: Department of Forensic Science, Central Police University, Taoyuan, Taiwan. cwen@sun4.cpu.edu.tw
authors.forename: Che-Yen
authors.initials: CY
authors.lastname: Wen
authors.forename: Chiu-Chung
authors.initials: CC
authors.lastname: Yu
mesh_terms: D003878:Dermatoglyphics; D005554:Forensic Medicine / Q000379:methods*; D006801:Humans; D015233:Models, Statistical; D012815:Signal Processing, Computer-Assisted