Sex differences from fingerprint ridge density in Chinese and Malaysian population

Nayak, Vinod C; Rastogi, Prateek; Kanchan, Tanuj; Yoganarasimha, K.; Kumar, G. Pradeep; Menezes, Ritesh G.

doi:10.1016/j.forsciint.2009.12.055

Cited by 87 publications

(69 citation statements)

References 8 publications

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“…The RD has been previously reported for forensic examinations aid in sex determination in multiple populations, for example Caucasian American, African American, Indian, Malaysian, Chinese, and Spanish ethnic groups. Higher RD in females than males in a given area was declared in earlier studies [4][5][6][7]. The RD, a number of finger ridges counted on the diagonal line drawn between a square of 25 mm 2 on the core of fingerprint image, varies among populations and sexes especially in people over 12 years old [8].…”

Section: Introductionmentioning

confidence: 75%

Variability of Finger Ridge Density among Thai Adolescents

Nanakorn¹,

Kutanan²

2012

J Forensic Res

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Finger ridge density (RD) is the number of finger ridges that touch the diagonal line drawn between a square of 25 mm 2 which is placed on the core of the fingerprint image. It has been useful as a sex determination aid in forensic practice as its values are significantly higher in females than males. The present study was aimed at investigating the RD of Thai adolescents aged between 10 and 12 years old. Subjects were 130 schoolboys and 130 schoolgirls were randomly selected and signed informed consent forms prior to printing each individual's ten fingers by using the adhesive transparent tape technique. The Microsoft Word program was applied for precise counting of RD. The mean RD differences between left and right hands, boys and girls, radial and ulnar areas were statistically tested. The likelihood ratio was computed to obtain the probability inferences of sex, and posterior probabilities were estimated using Bayes' theorem. Results revealed as follows: (1) The mean RDs (ridges per 25 mm 2 ) of boys and girls were not significantly different across the radial (15.89 vs. 16.19, respectively) and ulnar areas (15.84 vs. 16.00, respectively). For each sex, mean RDs in the radial and the ulnar were not statistically different. (2) The mean RDs in both sexes were greater in the left hand fingers compared to the right hand, and were statistically significant only in girls. (3) For the ulnar area, the RD of 13 or less is most likely to be of from male origin and that of 17 or more has a low probability of being of female origin. Comparing the radial area, an RD of 14 or less has a low probability of being of male origin while a weak probability of the RD of 17 or more is most likely being of female origin.

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Section: Introductionmentioning

confidence: 75%

Variability of Finger Ridge Density among Thai Adolescents

Nanakorn¹,

Kutanan²

2012

J Forensic Res

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“…Based on previous research [3][4] [5][6] [7][8], ridge density is the criteria which is most prominent to differentiate the sex of a person [9]. From these studies, we can infer that ridge density is a good feature for identifying the gender.…”

Section: Introductionmentioning

confidence: 98%

“…The statistics of dermatologlyphics differ between gender, ethical groups, and age categories [1] [2]. These categories were defined during the early investigation of fingerprint structure by looking at the intensity of ridges and ridge count [3][4] [5][6] [7] [8].…”

Section: Introductionmentioning

confidence: 99%

Development of a Fingerprint Gender Classification Algorithm Using Fingerprint Global Features

Abdullah¹,

Rahman²,

Abas³

et al. 2016

ijacsa

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Abstract-In forensic world, the process of identifying and calculating the fingerprint features is complex and take time when it is done manually using fingerprint laboratories magnifying glass. This study is meant to enhance the forensic manual method by proposing a new algorithm for fingerprint global feature extraction for gender classification. The result shows that the new algorithm gives higher acceptable readings which is above 70% of classification rate when it is compared to the manual method. This algorithm is highly recommended in extracting a fingerprint global feature for gender classification process.

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“…They commonly determine ridge related features [4], [5], analyze frequency domain [6], and implement 2D Discrete Wavelet Transforms [7].…”

Section: Introductionmentioning

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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Sex differences from fingerprint ridge density in Chinese and Malaysian population

Cited by 87 publications

References 8 publications

Variability of Finger Ridge Density among Thai Adolescents

Variability of Finger Ridge Density among Thai Adolescents

Development of a Fingerprint Gender Classification Algorithm Using Fingerprint Global Features

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

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