Topological Variability of Fingerprint Ridge Density in a Sub‐Saharan Population Sample for Application in Personal Identification

Gutiérrez‐Redomero, Esperanza; Quirós, Juan A.; Rivaldería, Noemí; Alonso, María C.

doi:10.1111/1556-4029.12092

Cited by 25 publications

(13 citation statements)

References 49 publications

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“…The presence of prints on pottery is one of chance and the attention a potter cared to give them, but epidermal prints do occur on ancient ceramics. While they may not be rare, they are rarely studied despite consistent research by forensic scholars on developing and refining methods of identifying the age and sex of individuals from epidermal finger and palm prints [4][5][6][7][8][9].…”

Section: Introductionmentioning

confidence: 99%

Fingerprint evidence for the division of labour and learning pottery-making at Early Bronze Age Tell eṣ-Ṣâfi/Gath, Israel

et al. 2020

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The organization of craft production has long been a marker for broader social, economic and political changes that accompanied urbanism. The identity of producers who comprised production groups, communities, or workshops is out of reach using conventional archaeological data. There has been some success using epidermal prints on artefacts to identify the age and sex of producers. However, forensic research indicates that a combination of ridge breadth and ridge density would best identify the age and sex of individuals. To this end, we combine mean ridge breadth (MRB) and mean ridge density (MRD) to distinguish the age and sex of 112 fingerprints on Early Bronze Age (EB) III pottery from the early urban neighbourhood at Tell eṡ-Ṡ â fi/Gath, Israel, dating to a 100 year time span. Our analysis accounts for the shrinkage of calcareous fabrics used to make six type of vessels, applies a modified version of the Kamp et al. regression equation to the MRB for each individual print, and infers sex by correlating MRD data to appropriate modern reference populations. When the results are combined, our analyses indicate that most fingerprints were made by adult and young males and the remainder by adult and young females. Children's prints are in evidence but only occur on handles. Multiple prints of different age and sex on the same vessels suggest they were impressed during the training of young potters. Production appears dominated by adult and young males working alone, together, and in cooperation with adult and/or young females. Vessels with prints exclusively by females of any age are rare. This male dominant cooperative labour pattern contrasts recent studies showing that adult women primarily made Neolithic figurines in Anatolia, and more females than males were making pottery prior to the rise of city-states in northern Mesopotamia.

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Section: Introductionmentioning

confidence: 99%

Fingerprint evidence for the division of labour and learning pottery-making at Early Bronze Age Tell eṣ-Ṣâfi/Gath, Israel

et al. 2020

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“…The research of gender classification based on fingerprint was conducted in some countries, such as in sub-Saharan region [11], Turkey [12], [13], Thai [14], Malaysia [15] and much more.…”

Section: Gender Classification Based On Ridge Densitymentioning

confidence: 99%

A Short Review of Gender Classification based on Fingerprint using Wavelet Transform

Suwarno¹,

Santosa²

2017

ijacsa

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Abstract-In some cases, knowing the gender of fingerprint owner found in criminal or disaster scene is advantageous. Theoretically, if the number of the male and female fingerprints in a database is equal, then the identification process of a fingerprint on that database would be two times faster. Some methods have been used to classify gender based on the fingerprint. Most of the method is based on ridge density. This method showed good result. However, it is sensitive to the location of the fingerprint area where ridge density is determined. This paper reviews some literature that used wavelet transform to generate features of a fingerprint. As far as what we found in literature, the number of papers on this topic is very limited. However, based on the literature we reviewed, wavelet transform gives some advantages compared to ridge density counting.

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“…Researchers have not only tried sex differentiation with prints but have also observed overall intra-and interindividual variability in this trait. 8,10,11 Variations have been observed in the ridge density of different areas of the fingerprint, a similar area of fingerprints from different fingers, left and right palms, and different areas of the palms, left and right footprints, as well as in different areas of footprints.…”

Section: Introductionmentioning

confidence: 96%

“…Ridge density is defined as the ridge counts in a defined area on a fingerprint, palm-print or footprint. A few studies have been conducted on the variability of fingerprint [2][3][4][5][6][7][8] and palm-print ridge density 9,10 in individuals and their possible use in the estimation of sex in forensic examinations. Sex differentiation using ridge density is based upon the fact that females tend to have finer ridge details than do males.…”

Section: Introductionmentioning

confidence: 99%

Variability of footprint ridge density and its use in estimation of sex in forensic examinations

et al. 2014

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The present study deals with a comparatively new biometric parameter of footprints called footprint ridge density. The study attempts to evaluate sex-dependent variations in ridge density in different areas of the footprint and its usefulness in discriminating sex in the young adult population of north India. The sample for the study consisted of 160 young adults (121 females) from north India. The left and right footprints were taken from each subject according to the standard procedures. The footprints were analysed using a 5 mm × 5 mm square and the ridge density was calculated in four different well-defined areas of the footprints. These were: F1 - the great toe on its proximal and medial side; F2 - the medial ball of the footprint, below the triradius (the triradius is a Y-shaped group of ridges on finger balls, palms and soles which forms the basis of ridge counting in identification); F3 - the lateral ball of the footprint, towards the most lateral part; and F4 - the heel in its central part where the maximum breadth at heel is cut by a perpendicular line drawn from the most posterior point on heel. This value represents the number of ridges in a 25 mm(2) area and reflects the ridge density value. Ridge densities analysed on different areas of footprints were compared with each other using the Friedman test for related samples. The total footprint ridge density was calculated as the sum of the ridge density in the four areas of footprints included in the study (F1 + F2 + F3 + F4). The results show that the mean footprint ridge density was higher in females than males in all the designated areas of the footprints. The sex differences in footprint ridge density were observed to be statistically significant in the analysed areas of the footprint, except for the heel region of the left footprint. The total footprint ridge density was also observed to be significantly higher among females than males. A statistically significant correlation is shown in the ridge densities among most areas of both left and right sides. Based on receiver operating characteristic (ROC) curve analysis, the sexing potential of footprint ridge density was observed to be considerably higher on the right side. The sexing potential for the four areas ranged between 69.2% and 85.3% on the right side, and between 59.2% and 69.6% on the left side. ROC analysis of the total footprint ridge density shows that the sexing potential of the right and left footprint was 91.5% and 77.7% respectively. The study concludes that footprint ridge density can be utilised in the determination of sex as a supportive parameter. The findings of the study should be utilised only on the north Indian population and may not be internationally generalisable.

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Topological Variability of Fingerprint Ridge Density in a Sub‐Saharan Population Sample for Application in Personal Identification

Cited by 25 publications

References 49 publications

Fingerprint evidence for the division of labour and learning pottery-making at Early Bronze Age Tell eṣ-Ṣâfi/Gath, Israel

Fingerprint evidence for the division of labour and learning pottery-making at Early Bronze Age Tell eṣ-Ṣâfi/Gath, Israel

A Short Review of Gender Classification based on Fingerprint using Wavelet Transform

Variability of footprint ridge density and its use in estimation of sex in forensic examinations

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