Personal identification based on finger-vein features

Yang, Jinfeng; Shi, Yihua; Yang, Jie

doi:10.1016/j.chb.2010.10.029

Cited by 73 publications

(50 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Here, we used the method proposed in [20] for Gaborbased feature extraction. The eight filtered images are generated by 2D convolution operation between a ROI and a Gabor filter at eight orientations, and then using the average absolute deviation (AAD) of each block to represent the local features of a filtered fingervein image.…”

Section: B Content-based Featurementioning

confidence: 99%

“…Recently, many approaches have been proposed for fingervein feature extraction [17], [18], [19], [20]. These approaches are useful in finger-vein feature analysis.…”

Section: Feature Analysismentioning

confidence: 99%

“…Compared with traditional biometric technique, the finger-vein technique exists some exceptional advantages in application, finger-vein patterns are superior in liveness, anti-counterfeiting and friendliness apart from uniqueness, universality, permanence and measurability. So finger-vein recognition has drawn substantial attention in personal identification [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19], [20], [21].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A Hierarchal Framework for Finger-Vein Image Classification

Tan

Yang

Shi

et al. 2013

2013 2nd IAPR Asian Conference on Pattern Recognition

Self Cite

View full text Add to dashboard Cite

For personal identification, the biometric systems based on finger-vein pattern have been successfully used in many applications. The concern for the system efficiency over a large database should not be negligible in the real situation. So, categorizing the finger-vein images to different classes is helpful for reducing pattern matching cost. In this paper, we propose a level-based framework for roughly and automatically categorizing finger-vein images. The proposed level-based framework consists of two layers in classifying finger-vein images. In this framework, the imaging qualities and the image contents are respectively used for the first layer and second layer image feature representation. And the k-means algorithm is adopted for automatic finger-vein image clustering. Using SVM scheme, we can achieve 99% CCR (correct classification rate) over a large image database. Finally, for comparison, the POC (Phase-Only-Correction) matching algorithm is used. Experimental results show that the proposed method has a good performance in the improving recognition efficiency as well as recognition accuracy.

show abstract

Section: B Content-based Featurementioning

confidence: 99%

“…Recently, many approaches have been proposed for fingervein feature extraction [17], [18], [19], [20]. These approaches are useful in finger-vein feature analysis.…”

Section: Feature Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Hierarchal Framework for Finger-Vein Image Classification

Tan

Yang

Shi

et al. 2013

2013 2nd IAPR Asian Conference on Pattern Recognition

Self Cite

View full text Add to dashboard Cite

show abstract

“…[107]. There are three types of scanning devices that are used for capturing the hand and finger veins.…”

Section: B Hand / Finger Veins Based Systemsmentioning

confidence: 99%

Veins Based Personal Identification Systems: A Review

Mishra¹,

Mishra²,

Agrawal³

2016

IJISA

View full text Add to dashboard Cite

Abstract-Identification of people among each other has always been a tough and challenging task for the researchers. There are many techniques which are used for identify ing a person but biometric technique is the standard one which allows us for online identification of individuals on the basis of their physiological and behavioral features. The veins based systems include finger veins, face veins, palm veins, head veins, heart veins, iris, palatal veins of the rogue etc. The multi-veins based systems use the veins of different physiological traits for identifying a person. This paper illustrates an overview of veins based personal identificat ion systems . The perfo rmance of different single and multi-veins based identification systems are analyzed in this paper. The features like reliability, security, accuracy, robustness and long term stability along with the strengths and weaknesses of various veins based biometric approaches were taken into considerations while analy zing the results of existing research papers published so far. At last the future research directions in the field of veins based identification systems have also been outlined.

show abstract

“…Second, the quality of the captured vein pattern image is not influenced by skin condition such as sweat, dryness and skin diseases. Lastly, finger vein image capturing is hygienic because it does not require contact between the finger and sensor [5,6]. Due to above benefits finger vein recognition has become popular, promising and efficient biometric for personal identification [2,5].…”

Section: Introductionmentioning

confidence: 99%

Finger Vein Recognition using Rotated Wavelet Filters

Shrikhande¹,

Fadewar²

2016

IJCA

View full text Add to dashboard Cite

Finger vein biometric have been recognized as the most effective and promising recognition method due to its accuracy and security. This paper discusses a method for finger vein image features extraction using 2-D Rotated Wavelet Filters (RWF) and Discrete Wavelet Transform (DWT) jointly. A set of 2-D RWF filters improves characterization of diagonally oriented texture features from a finger vein image. The 2-D RWF and DWT jointly used for decomposition of a finger vein image ROI up to third level. The standard deviation and energy of each subband from every decomposition level are used for the creation of features vector. Then Canberra distance classifier is used for the classification of finger vein images. The performance of this method has evaluated on the standard finger vein image database of Shandong University (SDUMLA), China. Experimental results have shown that the method with RWF and DWT jointly gives better results as compare to the traditional DWT based methods.

show abstract

Personal identification based on finger-vein features

Cited by 73 publications

References 16 publications

A Hierarchal Framework for Finger-Vein Image Classification

A Hierarchal Framework for Finger-Vein Image Classification

Veins Based Personal Identification Systems: A Review

Finger Vein Recognition using Rotated Wavelet Filters

Contact Info

Product

Resources

About