The fingerprints and face recognition are two biometric processes that comprise methods for uniquely recognizing humans based on certain number of intrinsic physical or behavioral traits.The objectives of the study we...The fingerprints and face recognition are two biometric processes that comprise methods for uniquely recognizing humans based on certain number of intrinsic physical or behavioral traits.The objectives of the study were to predict the facial height(FH),facial width,and ratios from thumbprints ridge count and its possible applications.This was a cross-sectional study.A total of 457 participants were recruited.A fingerprint live scanner was used to capture the plain thumbprint.The facial photograph was captured using a digital camera.Pearson’s correlation analysis was used for the relationship between thumbprint ridge density and facial linear dimensions.Step‑wise linear multiple regression analysis was used to predict facial distances from thumbprint ridge density.The result showed that in males the right ulnar ridge count correlates negatively with lower facial width(LFW),upper facial width/upper FH(UFW/UFH),lower FH/FH(LFH/FH),and positively with UFH and UFW/LFW.The right and left proximal ridge counts correlate with LFW and UFH,respectively.In males,the right ulnar ridge count predicts LFW,UFW/LFW,UFW/UFH,and LFH/FH.Special upper face height I,LFW,height of lower third of the face,UFW/LFW was predicted by right radial ridge counts.LFH,height of lower third of the face,and LFH/FH were predicted from left ulnar ridge count whereas left proximal ridge count predicted LFW.In females only,the special upper face height I was predicted by right ulnar ridge count.In conclusion,thumbprint ridge counts can be used to predict FH,width,ratios among Hausa population.The possible application of fingerprints in facial characterization for used in human biology,paleodemography,and forensic science was demonstrated.展开更多
This study assessed the sex-based relationship and prediction pattern between fingerprint patterns,ridge counts,and learning disability(LD).This cross-sectional study recruited 300 students(150 LD and 150 non-LD)aged ...This study assessed the sex-based relationship and prediction pattern between fingerprint patterns,ridge counts,and learning disability(LD).This cross-sectional study recruited 300 students(150 LD and 150 non-LD)aged between 3 and 29 years.The fingerprint patterns(arch,whorl,ulnar loop,and radial loop)and the ridge count:total finger ridge count(TFRC),absolute ridge count(ARC),ulnar ridge count(URC),and radial ridge count(RRC)were accessed.Students with LD showed a significantly higher whorl and a significantly lower ulnar loop than students without LD.There is a significant association of whorl pattern in the first right finger of subjects with LD compared to non-LD counterparts.TFRC,ARC,and URC were significantly higher in females with LD than non-LD females(P=0.01,0.03,and 0.001).Males with LD showed significantly lower TFRC,RRC,and URC counts than the non-LD males(P=0.02,0.01,and 0.001).TFRC can predict LD in males(odds ratio[OR]=1.010,P=0.032)and females(OR=0.993,P=0.012).Fingerprint pattern and ridge counts are sexually dimorphic in subjects with or without LD.TFRC and whorl fingerprint patterns may be vital predictive and screening tools for LD in males and females.展开更多
基金sponsored by Bayero University Research Grant UnitTertiary Education Trust Fund(TETfund)of Nigeria.
文摘The fingerprints and face recognition are two biometric processes that comprise methods for uniquely recognizing humans based on certain number of intrinsic physical or behavioral traits.The objectives of the study were to predict the facial height(FH),facial width,and ratios from thumbprints ridge count and its possible applications.This was a cross-sectional study.A total of 457 participants were recruited.A fingerprint live scanner was used to capture the plain thumbprint.The facial photograph was captured using a digital camera.Pearson’s correlation analysis was used for the relationship between thumbprint ridge density and facial linear dimensions.Step‑wise linear multiple regression analysis was used to predict facial distances from thumbprint ridge density.The result showed that in males the right ulnar ridge count correlates negatively with lower facial width(LFW),upper facial width/upper FH(UFW/UFH),lower FH/FH(LFH/FH),and positively with UFH and UFW/LFW.The right and left proximal ridge counts correlate with LFW and UFH,respectively.In males,the right ulnar ridge count predicts LFW,UFW/LFW,UFW/UFH,and LFH/FH.Special upper face height I,LFW,height of lower third of the face,UFW/LFW was predicted by right radial ridge counts.LFH,height of lower third of the face,and LFH/FH were predicted from left ulnar ridge count whereas left proximal ridge count predicted LFW.In females only,the special upper face height I was predicted by right ulnar ridge count.In conclusion,thumbprint ridge counts can be used to predict FH,width,ratios among Hausa population.The possible application of fingerprints in facial characterization for used in human biology,paleodemography,and forensic science was demonstrated.
文摘This study assessed the sex-based relationship and prediction pattern between fingerprint patterns,ridge counts,and learning disability(LD).This cross-sectional study recruited 300 students(150 LD and 150 non-LD)aged between 3 and 29 years.The fingerprint patterns(arch,whorl,ulnar loop,and radial loop)and the ridge count:total finger ridge count(TFRC),absolute ridge count(ARC),ulnar ridge count(URC),and radial ridge count(RRC)were accessed.Students with LD showed a significantly higher whorl and a significantly lower ulnar loop than students without LD.There is a significant association of whorl pattern in the first right finger of subjects with LD compared to non-LD counterparts.TFRC,ARC,and URC were significantly higher in females with LD than non-LD females(P=0.01,0.03,and 0.001).Males with LD showed significantly lower TFRC,RRC,and URC counts than the non-LD males(P=0.02,0.01,and 0.001).TFRC can predict LD in males(odds ratio[OR]=1.010,P=0.032)and females(OR=0.993,P=0.012).Fingerprint pattern and ridge counts are sexually dimorphic in subjects with or without LD.TFRC and whorl fingerprint patterns may be vital predictive and screening tools for LD in males and females.
