Sibling and non-sibling fingerprints comparison of Pakhtun population of Swat district, KP, Pakistan

Subhan Uddin, Noor Ullah Khan, Murad Ali Rahat, Aftab Ahmad, Fazal Akbar, Naseer Ullah, Muzafar Shah, Akhtar Rasool, Muhammad Israr

Abstract


Background: Fingerprint and other ridges are considered to be the best forensic science tool for identification of humans, alive or dead, and even for decomposed bodies. These fingerprint ridges exhibit various static features throughout life which reflect the person biology. This branch gained immense importance since the past few decades in congenital abnormality. This study was to carry out fingerprints analysis of sibling and non-sibling for differentiation and gender identification.

Methods: A total of 80 pairs of fingerprints (1600 prints) were collected from persons aged 15 to 30 years using rolling method. Out of which 20 pairs were brother-brother, 20 were sister-sister, 20 were brother-sister and 20 Pairs were random. Each fingerprint was analyzed for the gender identification on the basis of minutiae, ridge density and types. All the fingerprints were analysed using ACE-V method. After comparison SPSS software was used for further analysis.

Results: Our result showed that the types of fingerprints identified was whorl (50%) followed by loop (45.25%), arch (4.5%) and 0.25% of the accidental type. The dominant type was whorl while accidental was the least common type of fingerprints. Statistical analysis showed that between the groups, brother-brother and sister-sister was significant while rest of the groups was not significant. Moreover, greater ridge density was observed in female as compared to male.

Conclusion: It is concluded that the sibling fingerprints had greater similarity as compared to non-sibling, however both male and female fingerprints were significantly different in term of ridges density. This study may be useful in crime scene investigation.

Keywords: Forensics; Fingerprint ridge density; Fingerprint type; Gender identification 


Full Text:

PDF

References


Acree MAJFsi. Is there a gender difference in fingerprint ridge density? Forensic Science International, (1999); 102(1): 35-44.

Ceyhan EB, Sağiroğlu Ş. Gender inference within Turkish population by using only fingerprint feature vectors; 2014. IEEE. pp. 146-150.

Gutiérrez-Redomero E, Alonso C, Romero E, Galera VJFSI. Variability of fingerprint ridge density in a sample of Spanish Caucasians and its application to sex determination. Forensic science international, (2008); 180(1): 17-22.

Nayak VC, Rastogi P, Kanchan T, Yoganarasimha K, Kumar GP, et al. Sex differences from fingerprint ridge density in Chinese and Malaysian population. Forensic Science International, (2010); 197(1-3): 67-69.

Mulvihill JJ, Smith DWJTJop. The genesis of dermatoglyphics. The Journal of Pediatrics, (1969); 75(4): 579-589.

Babler WJBdoas. Embryologic development of epidermal ridges and their configurations. Birth defects original article series, (1991); 27(2): 95-112.

Badawi AM, Mahfouz M, Tadross R, Jantz RJI. Fingerprint-Based Gender Classification. (2006); 6(8): l.

Sudesh Gungadin MJIJoMU. Sex determination from fingerprint ridge density. Internet Journal of Medical Update, (2007); 2(2): 1-4.

Maltoni D, Maio D, Jain A (2003) S. Prabhakar,“4.3: Minutiae-based Methods’(extract) from Handbook of Fingerprint Recognition”. Springer, New York.

Dauvergne M, Turner JJJCCfJS. Police-reported crime statistics in Canada, 2009. (2010); 30(2): 1D.

India PSJMOHA, Government Of India, New Delhi. National Crime Records Bureau. (2011).

JJUSFBoI H. The science of fingerprints: Classification and uses. (2006).

Nithin M, Balaraj B, Manjunatha B, Mestri SCJJoF, Medicine L. Study of fingerprint classification and their gender distribution among South Indian population. Journal of Forensic and Legal Medicine, (2009); 16(8): 460-463.

Sumathi G, Jeyasekaran G, Shakila RJ, Sivaraman B, Arunkumar G, et al. Molecular identification of grouper species using PCR-RFLP technique. Food Control, (2015); 51300-306.

Rajesh DG, Punithavalli M. Wavelets and Gaussian mixture model approach for gender classification using fingerprints; 2014. IEEE. pp. 522-525.

Tom RJ, Arulkumaran T, Scholar MJIJoET, Technology. Fingerprint based gender classification using 2D discrete wavelet transforms and principal component analysis. International Journal of Engineering Trends and Technology, (2013); 4(2): 199-203.

Wadhwa R, Kaur M, Singh KJIJoE. Age and Gender Determination from Finger Prints using RVA and dct coefficients. IOSR Journal of Engineering, (2013); 3(8): 2250-3021.

Ashbaugh DR. Quantitative-qualitative friction ridge analysis: an introduction to basic and advanced ridgeology. 1999; CRC press.

Purkait RJJ. Fingerprint Classification: A comparative study among Mundas and Lodhas. Medico-legal Update, (2003); 14(1): 31-32.

Rahat MA, Khan AS, Bibi R, Haris M, Akbar F, et al. Monozygotic and Dizygotic Twins Differences in Fingerprint Patterns of Swat District. Advancements in Life Sciences, (2020);

(4): 232-236.

Gangadhar M, Rajasekhara Reddy KJMiI. Finger dermatoglyphics of Adikarnatakas: a scheduled caste population of Mysore City, Karnataka. Man in India, (2003); 83(1-2): 183-193.

Igbigbi PS, Msamati BCJMSM. Palmar and digital dermatoglyphics of indigenous black Zimbabweans. Medical science monitor, (2002); 8(11): CR757-CR761.

Li S, Jain A (2009) Encyclopedia of biometrics. 2009. Springer Verlag.

Brock J-AK, Allen VM, Kieser K, Langlois SJJoO, Canada G. Family history screening: use of the three generation pedigree in clinical practice. Journal of obstetrics and gynaecology Canada, (2010); 32(7): 663-672.

Harden KP, Hill JE, Turkheimer E, Emery REJBg. Gene-environment correlation and interaction in peer effects on adolescent alcohol and tobacco use. Behavior genetics, (2008); 38(4): 339-347.

Rastogi P, Pillai KRJJoIAoFM. A study of fingerprints in relation to gender and blood group. Indian Journal of Forensic and Community Medicine, (2010); 32(1): 11-14.

DJA C. Facts. ABO blood and human origins. (2008); 37(2): 10.

Floris GJAjopa. Sex and side differences and correlations between quantitative palmar characteristics in a sample Sardinian population. American journal of physical anthropology, (1975); 42(2): 277-280.




DOI: http://dx.doi.org/10.62940/als.v9i1.1279

Refbacks

  • There are currently no refbacks.