Title :
Using Leg Geometry to Align Androgenic Hair Patterns in Low Resolution Images for Criminal and Victim Identification
Author :
Chan, F.K.-S. ; Kong, A.W.-K.
Author_Institution :
Sch. of Comput. Eng., Nanyang Technol. Univ., Singapore, Singapore
Abstract :
Identifying criminals and victims in digital media can be very challenging when neither their faces nor tattoos are observable. These criminals and victims can be masked gunmen, paedophiles, and victims in child pornographic images. Though skin marks and blood vessel patterns hidden in color images have been proposed to address this problem, they have different limitations. Blood vessel patterns are not suitable for subjects with high concentration of body fat or melanin and skin marks are not suitable for the cases where only low resolution images are available. A recent paper pointed out that androgenic hair, which is also called body hair, and its follicles can be used as biometric traits and demonstrated that androgenic hair patterns in low resolution images are effective for personal identification. In that study, viewpoint and pose variations were ignored, but these variations are unavoidable in real cases. To overcome the weaknesses of the previous method, this paper proposes an algorithm based on geometric information for aligning androgenic hair patterns on lower legs. The experimental results on 1,138 low resolution images from 283 different legs show that the proposed alignment algorithm offers more than 5% improvement.
Keywords :
criminal law; geometry; image resolution; androgenic hair pattern alignment; blood vessel patterns; body fat; body hair; child pornographic images; color images; criminal identification; digital media; follicles; leg geometry; low resolution images; masked gunmen; melanin; paedophiles; personal identification; skin marks; victim identification; Biomedical imaging; Hair; Image edge detection; Image resolution; Legged locomotion; Sampling methods; Skin; Forensics; biometrics; blood vessels; skin marks;
Conference_Titel :
Pattern Recognition (ICPR), 2014 22nd International Conference on
Conference_Location :
Stockholm
DOI :
10.1109/ICPR.2014.94