A Fingerprint Recognition Algorithm Based on Principal Component Analysis

Yongxu, Wang; Ao, Xinyu; Du, Yuanfeng; Li, Yongping

doi:10.1109/tencon.2006.344032

Cited by 15 publications

(6 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…PCA is the one of the effective method to reduce or tune the dimension in the images. Here, it is calculated for lower dimensional basis to signify the data [21].…”

Section: Reduction In Dimensionmentioning

confidence: 99%

Evaluation of Fingerprint Liveness Detection by Machine Learning Approach - A Systematic View

Adam¹,

Sathesh²

2021

JISMAC

View full text Add to dashboard Cite

Recently, fake fingerprint detection is a challenging task in the cyber-crime sector in any developed country. Biometric authentication is growing in many sectors such as internet banking, secret file locker, etc. There spoof fingerprint detection is an essential element that is used to detect spot-on fingerprint analysis. This article focuses on the implementation and evaluation of suitable machine learning algorithms to detect fingerprint liveness. It also includes the comparative study between Ridge-let Transform (RT) and the Machine Learning (ML) approach. This article emphasis on research and analysis of the detection of the liveness spoof fingerprint and identifies the problems in different techniques and solutions. The support vector machine (SVM) classifiers work with indiscriminate loads and confined grayscale array values. This leads to a liveness report of fingerprints for detection purposes. The SVM methodology classifies the fingerprint images among more than 50K of real and spoof fingerprint image collections based on this logic. Our proposed method achieves an overall high accuracy of detection of liveness fingerprint analysis. The ensemble classifier approach model is proving an overall efficiency rate of 90.34 % accurately classifies samples than the image recognition method with RT. This recommended method demonstrates the decrement of 2.5% error rate when compared with existing methods. The augmentation of the dataset is used to improve the accuracy to detect. Besides, it gives fake fingerprint recognition and makes available future direction.

show abstract

“…PCA is the one of the effective method to reduce or tune the dimension in the images. Here, it is calculated for lower dimensional basis to signify the data [21].…”

Section: Reduction In Dimensionmentioning

confidence: 99%

Evaluation of Fingerprint Liveness Detection by Machine Learning Approach - A Systematic View

Adam¹,

Sathesh²

2021

JISMAC

View full text Add to dashboard Cite

show abstract

“…For that, we require some other approach to remove false minutiae points caused by poor quality. We have applied the Principal Component Analysis (PCA) technique for improving the recognition rate of fingerprints [23].…”

Section: = (Xiyiθiti)mentioning

confidence: 99%

A Hybrid Privacy Preserving Scheme Using Finger Print Detection in Cloud Environment

Verma¹,

Chakraborty²

2019

ISI

View full text Add to dashboard Cite

Cloud computing provides a new paradigm of computing. It offers a scalable, manageable and huge pool of resources that can be accessed by users from anywhere anytime. It also ensures the integrity of data stored on the cloud. But ensuring the confidentiality and integrity of sensitive information is still a big challenge. To overcome this challenge, a hybrid two-phase security system for preserving the privacy of data on the cloud has been proposed. The hybrid approach combines feature extraction and encryption techniques to enhance the security of accessing data from the cloud. At first, the minutiae point has been extracted from the biometric fingerprint, locally collected from the state university in Northern India. The private key has been finalized by generating an elliptic curve using the minutiae point for achieving better encryption of fingerprint. The effectiveness of the approach has been tested in terms of similarity score, False Matching Ratio (FMR), False Non Matching Ratio (FNMR) and recognition accuracy, when applied on the local fingerprint database. The evidence of the outcomes suggests that the proposed technique ensures relatively improved security and privacy of data in the cloud system as compared to some recent state-of-art methods.

show abstract

“…This process also required more than one fingerprints for recognizing the authenticated person. Research has also taken on genetic algorithm based fingerprint recognition system [62][63][64][65]. But again same fingerprint problems may generate here because of one quite same fingerprints.…”

Section: Related Workmentioning

confidence: 99%

An Advanced Door Lock Security System using Palmtop Recognition System

Nafi¹,

Kar²,

Hoque³

2012

IJCA

View full text Add to dashboard Cite

Biometric technology is used to identify a person based on his/her physical behavioral characteristics. One of the extensive uses of biometric technology is a fingerprint recognition system. The technology has broad use mainly for its easiness, reliability and accuracy in human identification process. This paper presents work done on minutiae based palmtop recognition system for automatic door open and locking system. Here, the palmtop recognition system works by taking an image of the person, partitioning it, processing it and finally verifying the person. This system provides input for an electric circuit. The circuitry system consists of two unique states; door open and door lock. The whole system basically uses extensive Image processing for minutiae based palmtop recognition. Thus reducing the probability of error in human recognition and solves maximum problems of fingerprint recognition. This paper shows a better solution for recognizing people, which helps to solve security related problems in human life.

show abstract

A Fingerprint Recognition Algorithm Based on Principal Component Analysis

Cited by 15 publications

References 8 publications

Evaluation of Fingerprint Liveness Detection by Machine Learning Approach - A Systematic View

Evaluation of Fingerprint Liveness Detection by Machine Learning Approach - A Systematic View

A Hybrid Privacy Preserving Scheme Using Finger Print Detection in Cloud Environment

An Advanced Door Lock Security System using Palmtop Recognition System

Contact Info

Product

Resources

About