Detailed Analysis of Footprint Geometry for Person Identification

Nain, Neeta; Singal, Gaurav

doi:10.1109/sitis.2017.47

Cited by 17 publications

(12 citation statements)

References 23 publications

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“…FRR (or, False Non Match Rate (FNMR)) refers to the rate at which the system incorrectly rejects access to an authorized person. On the other hand, the rate at which the system falsely authorizes a non-authorized person is termed as FAR (or, the False Match Rate (FMR)) [11]. Finally, the Accuracy governs the efficiency of the system in terms of its ability to identify a person which is dependent on the values of FRR and FAR both.…”

Section: Resultsmentioning

confidence: 99%

“…The second principal component provides the basis vector of next directions orthogonal to the first principal component and so on. The last dimension of this subspace captures the least amount of variance among the images based on the statistical characteristics of the targets [2], [8], [10], [11].…”

Section: ) Pcamentioning

confidence: 99%

“…It generally discards principal components with zero or near-zero eigenvalues. Hence, it results in dimensionality reduction [2], [8], [10], [11].…”

Section: ) Pcamentioning

confidence: 99%

“…Thirdly, it is never possible to forge the footprints of a person. Footprint Recognition Systems have many real-time applications like forensic sciences against intruder identifications, or identity verification of newborns to protect them from baby switching [3], [11]. It also can be easily implemented in temples or holy places where only designated barefooted persons are allowed to enter nearsacred deity idol place, to save from malicious attacks [6].…”

Section: Introductionmentioning

confidence: 99%

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Novel Distance Metric for Touch less Footprint Based Identification Technique

Gupta*¹,

Deepa²

2020

IJITEE

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In this fast-paced technology-driven today's era, biometrics is not the new buzzword in the information security domain. Biometrics uses any physiological or/ and behavioral attribute/s of an individual for personal identification and/or verification. In biometrics, so many traits, like a fingerprint, face, palm, retina, iris, ECG, gait, voice, and signature, etc., have been used from ages to uniquely identify a human being. Biometrics based on Footprints is the latest practice for personal identification. Like fingerprints and palmprints, footprints of individuals carry uniqueness; hence can be used in biometrics for personal recognition. This work investigates the powerfulness of footprints by extracting texture and shape features using Principal Component Analysis (PCA) method based upon Eigenfeet and introduces a new distance metric during the matching phase. Experimental results show that the new distance metric shows better results in comparison to the Euclidean, Manhattan and Mahalanobis distances.

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Section: Resultsmentioning

confidence: 99%

Section: ) Pcamentioning

confidence: 99%

“…It generally discards principal components with zero or near-zero eigenvalues. Hence, it results in dimensionality reduction [2], [8], [10], [11].…”

Section: ) Pcamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Novel Distance Metric for Touch less Footprint Based Identification Technique

Gupta*¹,

Deepa²

2020

IJITEE

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show abstract

“…Biometric features such as iris, face, DNA, voice, dental tissue , fingerprint, and footprint have proved to be sole to each person and constant all its lifetime. Biometrics system used to distinguish and detect individual based on biological and behavioral characteristics [2]. Footprint biometrics is an identity that could be applied usefully in crossing points at airport.…”

Section: Introductionmentioning

confidence: 99%

Swarm intelligent hyperdization biometric

Alhamdani

Ibrahim

2020

IJEECS

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At the last decade the importance of biometrics has been clearly configured due to its important in the daily life that starts from civil applications with security and recently terrorizing. A Footprint recognition is one of the effective personal identifications based on biometric measures. The aim of this research is to design a proper and reliable left human footprint biometrics system addressed (LFBS). In addition, to create a human footprint database which it is very helpful for numerous use such as during authentication. The existing footprint databases were very rare and limited. This paper presents a sturdy combined technique which merges between Image Processing with Artificial Intelligent technique via Bird Swarm Optimization Algorithm (BSA) to recognize the human footprint. The use of (BSA) enhance the performance and the quality of the results in the biometric system through feature selection. The selected features was treated as the optimal feature set in standings of feature set size. The visual database was constructed by capturing life RGB footprint images from nine person with ten images per person. The visual dataset images was pre-processed by successive operations. Chain Code is used with footprint binary image, then statistical features which represent the footprint features. These features were extracted from each image and stored in Excel file to be entered into the Bird Swarm Algorithm. The experimental results show that the proposed algorithm estimates, excellent results with a smaller feature set in comparison with other algorithms. Experimental outcomes show that our algorithm achieves well-organized and accurate result about 100% accuracy in relation with other papers on the same field.

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Person Identification Using Footprint Minutiae

Kushwaha

Nain

2019

Proceedings of 3rd International Conference on Computer Vision and Image Processing

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Detailed Analysis of Footprint Geometry for Person Identification

Cited by 17 publications

References 23 publications

Novel Distance Metric for Touch less Footprint Based Identification Technique

Novel Distance Metric for Touch less Footprint Based Identification Technique

Swarm intelligent hyperdization biometric

Person Identification Using Footprint Minutiae

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