Comparative and Identify the Kunckle Prints in Right and Left Hand of Male and Female, On the Basis of Bifurcation and Ridge Ending

Abstract

Knuckle prints are unique patterns, it contains ridges and furrows on the dorsal surface of the hand. Knuckle prints are used biometric identifier. These prints contain biological features like minutiae.The objective of this research is to investigate, the comparative analysis of knuckle prints in both hands of male and female individual. The study emphasizes the variations in ridge endings and bifurcations between right and left hand. Data collection involves gathering knuckle patterns from individuals aged 20 and above, with a target of 100 samples from each gender. The analysis focuses on the knuckle prints of the right and left hand of both genders, comparing the counts of ridge ending and bifurcation. The study aims to determine which hand exhibits a greater number of bifurcations and ridge endings, thereby facilitating personal and gender identification through knuckle prints. Samples are obtained via photography using a mobile camera, ensuring that the lens is used without flash during daylight against a black background. The captured knuckle print images are then converted to black and white to enhance their sharpness and clarity, utilizing the B and W 07 profiles in the Adobe Lightroom application. In here I count bifurcation and ridge ending in each figure and total count of right and left hand separately. The comparisons were made between the right and left hands, as well as between male and female subjects. The results indicate notable differences in the distribution of these minutiae between genders and hands.

Keywords

Introduction

A knuckle print refers to the distinct arrangement of ridges and grooves located on the back surface of the finger, particularly near the knuckle joints. While traditional identification methods have concentrated on the palm side of the fingers, knuckle prints provide an extra biometric feature useful for personal identification. Research indicates that these prints, similar to fingerprints, possess unique minutiae (specific ridge characteristics) that remain consistent throughout an individual's life.  A point where one ridge divides into two distinct branches is known as a bifurcation.  as shown in Figure 1.  One of the most significant characteristics that forensic experts use to distinguish individuals is this "forking" location.  Bifurcations significantly enhance a print's uniqueness due to every person has a different quantity and placement of them.  A ridge ending is a crucial detail that shows the exact location where a ridge abruptly stops.  as depicted in picture 2, ridge endings, like bifurcations, are crucial in creating a unique pattern for each individual. To identify and authenticate individuals is crucial for authenticity, and they are integrated with core data in many auto-fingerprint identifications.

Figure 1: Bifurcation

Figure 2: Ridge ending

These comparative learning goals are focused on the evaluations of the knuckle prints between men and women. Basic learning is aimed at the major difference in the rising biometric systems to simplify the gender identification in both hands and diversify the gender identification*. It showed that men have more ridge devices, as men and women have more ridge devices. The purpose of this study is to better understand the nature of the hand knuckle's behaviour to make it possible in forensic science and personal authentication technologies. To collect the knuckle patterns, collect 100 samples from each gender and emphasized individuals for persons and older. The left, the right, and knuckle prints will be the subject of the investigation, and the results of the participants will be compared between male and female. The study will be evaluated by linguists based on the risk of ending and distributing the ridge. When it comes to biometric and forensic settings. Additionally, the research will assess the symmetry of ridge features on both hands and examine the influence of handedness on ridge patterns, if applicable. Previous findings indicate a statistically significant difference in the number of ridge endings in the knuckle prints of males and females, as well as a notable difference in the number of bifurcations. Furthermore, there are considerable variations in ridge patterns between the left and right hands within both sexes. Ridge endings and bifurcations are established as reliable indicators for gender classification. Even though fingerprint analysis is a proven method, knuckle prints can be used as an extra or validating biometric characteristic. Especially when fingerprint quality is affected by environmental variables, wear, or injury.  The accuracy of forensic databases can be improved by analyzing knuckle prints along with details like ridge ends and bifurcations. This study minimizes the likelihood of misidentification and personal identification. [2]. knuckle prints have not been thoroughly investigated. Examining these prints provides a new opportunity to advance biometric identification systems and offers a novel viewpoint in forensic research. The study has important national and international forensic science ramifications.  It might strengthen border security, improve civil applications like secure access management, and improve criminal investigations.  

METHODOLOGY

This study compares the knuckle prints of males and females by examining the distribution of ridge endings and bifurcations to uncover any notable differences between the genders and between hands. To conduct the study, a mobile phone camera will be used to capture knuckle print images from 200 participants, evenly divided between 100 males and 100 females, all aged over 20 years. The images will be taken against a black background under natural daylight conditions to ensure clarity. Adobe Lightroom software will be used to enhance the images for better visibility of ridge detail. In the examination of a single finger knuckle print from the top to the bottom, the area is delineated from point A (top) to point B (bottom). As shown in figure 3, the sample collection process, each participant was directed to position their hand against a black background, ensuring that all five knuckle prints were distinctly visible. As shown in figure 4, in order to reduce glare and preserve the clarity of ridge features, photos were taken using a mobile phone's camera in natural daylight without the use of a flash.  Following collection, Adobe Lightroom was used to process the photos, converting them to black and white using the B and W 07 profile to improve clarity and sharpness.  As shown in figure 5, the next step involved a visual analysis of each knuckle print, with particular attention given to ridge endings and bifurcations. These features were counted from the top to the bottom of each finger to ascertain their frequency. The counts were subsequently categorized by gender to evaluate whether males or females displayed a greater prevalence of these ridge characteristics and difference in left and right hand.     

 

Figure 3: The examination Conducted surface from point A to B

Figure 4: Place both hands on the black

Figure 5: Using adobe lightroom app, the pictures were edited by applying a black and white filter and enhancing the clarity.

In male, total count of right ridge ending contain 3130 (47%). Total count of left ridge ending contain 3568 (53%). Ridge ending is more in left hand when compared to right hand.

In male, total count of right bifurcation contain 2790 (53%). Total count of left bifurcation contains 2260 (47%). Bifurcation is more in right hand when compared to left hand.

In female, total count of right ridge ending contain 3383 (57%). Total count of left ridge ending contain 2548 (43%). Ridge ending is more in right hand when compared to left hand.

In female, total count of right bifurcation contain 3305 (53%).  ridge ending is more in right hand when compared to right hand. Bifurcation is more in right hand when compared to left hand.

DISCUSSION

According to this study, I do comparative identification, on the basis of bifurcation and ridge ending in the right and left hand of males and females. In this research, the knuckle prints minutiae varies right and left hand in both males and females. In males, I found different minutiae, majority I was noticed ridge ending. It is more in left hand compared to right hand. It indicates simpler ridge structure in compared to right hand. Bifurcation was more dominate in right hand; it confirms greater degree of ridge complexity. In females, ridge ending and bifurcation greater in right hand compared to left hand. There are total of bifurcations 6688 are present in female and in male 5050 bifurcations are present. In the case of ridge ending there are total of 6698 ridge ending in males and 5931 ridge ending are seen in females.  This finding shows knuckles prints serve as an effective tool for identification of an individual. In forensic application knuckle prints shows distinct patterns of ridge ending and bifurcations across difference hands and gender. Knuckles prints are unique and introduce a new dimension to biometric identification method. The investigations were done by   Dhananjay Kumar Krishna Hegd, Priyanka Gupta (2024) this study aimed to identify the patterns based on the age and occupation. The study indicated that the, by changing the occupation and age clarity of the prints were decreased [1]. “Finger Knuckle Print Based Biometric Identification of a Person Using LBP and Bernoulli Classifier” this paper aimed to improve the biometric system by using the knuckle prints. They were taken the images of knuckle prints and entry to a database and then check it was working for the biometric system. The accuracy and specificity of the knuckle prints more than 95% [2]. The investigation was done by Achsah John with the title of “Comparative study of finger knuckle prints-pilot study”. The study aimed to identify the difference between males and females knuckle prints for identify the uniqueness. By analysing the prints, identify that the prints are unique in every individual. In males spacing between the ridge line was higher than female [3]. “Personal Identification using Finger Knuckle Orientation Features” this paper aimed to personal identification using finger images which exploits the orientation features from the random knuckle lines using finite Radon transform. These experimental results suggest that the orientation-based Knuckle Codes offer a promising and computationally simpler alternative for the automated personal identification. [4] “Finger Knuckle Print Recognition Techniques-A Survey” was done Esther Rani P, Shanmugalakshmi R with the aim to identify some of the methods used by the researchers for acquisition and techniques used for recognition systems based on finger knuckle print. The paper indicated that the Different image processing techniques that were used in personal identification biometric systems have been applied to finger knuckle print and shows promising results. it may be seen that fusion techniques results in high recognition rates. [5] These findings highlight the asymmetric structure between both hands and also influenced gender determination. Fingerprint and knuckle print minutia as same, both are used personal identification. In case of, the fingerprint difficult to collect we take knuckle print also.

CONCLUSION       

In this study the bifurcation and ridge ending seen in knuckle print of male and female were examined. In this study females have more frequency of bifurcation and ridge ending in right hand. In male ridge ending was higher in left hand and bifurcation in right hand. Knuckle prints are less commonly used in forensic field, because of other biometric identifier like fingerprint, palm print, lip prints etc. The ridge of knuckle prints contains individual variation. The individual variations are bifurcation and ridge ending etc.

In this comparative study, I observed

• Bifurcation is more frequently in female.
• In females, bifurcation and ridge ending is more in right hand.
• Ridge ending is more frequently in males.
• In males, bifurcation is more in right hand and ridge ending is more in left hand.

This study shows that knuckle print has unique Characteristics which is used for gender distinction and biometric identification. In future study we can expand our sample size and range of age by this we can get the correct findings. By using high resolution scanners, 3D knuckle imaging will increase the accuracy findings. In biometrics, we can also use knuckle prints for detection, classification and identification. knuckle prints are used personal identification in forensic field and criminal investigation. If there is no presence of fingerprint, knuckle prints are used personal identification. As same as fingerprint minutia are present in knuckle prints. In criminal investigation we find gender of the person through knuckle prints. Future study for knuckle prints is used for personal identification using biometrics. In this research help to future study for new biometric identifier. In criminal investigation, crucial role is identifying the victims or suscept. if we get unidentified body or unidentified suspect, we have to know about that person. Knuckle comparative study also help personal and gender identification. If we can not take fingerprint from the body, we take knuckle prints and then analysis, which turn to find that person. Any accidental case, Droney cases we have to very difficult to collect fingerprint, so that time we were compare to knuckle print date base and find the person. Fingerprints like knuckle prints are unique in nature.

REFERENCE

1. P. G. Dhananjay Kumar Krishna Hegde, “A study on identification of knuckle print,” International Journal of Forensic Medicine, vol. 6, no. 1, p. 9, 2024.
2. S. S. R. R. D. Soni M Rathod, “Finger Knuckle Print Based Biometric Identification of a Person Using LBP and Bernoulli Classifier,” International Journal of Scientific Development and Research, vol. 4, no. 10, p. 7, 2019.
3. A. John, “Comparative study of finger knuckle prints-pilot study,” Journal of Forensic Research, vol. 12, no. 9, p. 4, 2021.
4. Y. Z. Yingbo Zhou, “Personal Identification using Finger Knuckle Orientation Features,” Electronics Letters, vol. 45, no. 20, p. 9, 2009.
5. S. R. Esther Rani P, “Finger Knuckle Print Recognition Techniques-A Survey,” The International Journal of Engineering and Science, vol. 2, no. 11, p. 9, 2013.