Identification of persons by means of the Fourier spectra of the optical transmission binary models of the human irises

Muron, Ales; Kois, Petr; Pospíšil, Jiří

doi:10.1016/s0030-4018(01)01169-5

Cited by 9 publications

(3 citation statements)

References 3 publications

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“…Huang et al [14] use the values resulting from the independent coefficient analysis to characterize the iris texture. Muron et al [15] propose the codification of the whole information via the Fourier spectrum. Du et al [16] perform the feature extraction via computation of invariant local texture patterns.…”

Section: Iris Shown Inmentioning

confidence: 99%

Iris Recognition Using Segmental Euclidean Distances

Sayeed¹,

Hanmandlu²,

Ansari

et al. 2011

2011 Eighth International Conference on Information Technology: New Generations

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A novel segmentation method is developed for segmenting an Iris image into 6 circular segments after it has been cropped from an eye. Each segment is treated as a separate image to find Eigeniris and to recognize the Iris by the segmental Euclidean distance between the features of training and test samples computed from their segments. In addition to the Eigen features, the DCT and fuzzy features are extracted from the segments of iris images. Instead of segmental Euclidean distance as a classifier, the Support Vector Machine is also employed for the classification. The evaluation of performance on the CASIA V.2 database using Eigen, DCT and fuzzy features has resulted in the recognition rates of 93%, 98% and 95% respectively.

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Section: Iris Shown Inmentioning

confidence: 99%

Iris Recognition Using Segmental Euclidean Distances

Sayeed¹,

Hanmandlu²,

Ansari

et al. 2011

2011 Eighth International Conference on Information Technology: New Generations

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“…Other methods used in this area include: voice recognition 3 and palm recognition 4 , with the most common being finger print identification. The human eye also contains specific features in both the retina and the iris that may be used for recognition 5 .…”

Section: Introductionmentioning

confidence: 99%

Personal Identification Based on Vectorcardiogram Derived from Limb Leads Electrocardiogram

Lee

Chee

Kim

2012

Journal of Applied Mathematics

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We propose a new method for personal identification using the derived vectorcardiogram (dVCG), which is derived from the limb leads electrocardiogram (ECG). The dVCG was calculated from the standard limb leads ECG using the precalculated inverse transform matrix. Twenty-one features were extracted from the dVCG, and some or all of these 21 features were used in support vector machine (SVM) learning and in tests. The classification accuracy was 99.53%, which is similar to the previous dVCG analysis using the standard 12-lead ECG. Our experimental results show that it is possible to identify a person by features extracted from a dVCG derived from limb leads only. Hence, only three electrodes have to be attached to the person to be identified, which can reduce the effort required to connect electrodes and calculate the dVCG.

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“…In 1994, Daugman invented the automatic iris recognition system [8]. Over a decade, various algorithms have been proposed for iris recognition [9][10][11][12][13][14][15][16][17][18][19][20][21][22][23].…”

Section: Introductionmentioning

confidence: 99%

Using 2D Log-Gabor spatial filters for iris recognition

2006

SPIE Proceedings

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The iris is the colored ring of tissue behind the cornea and in front of the lens. The pattern within the iris is very unique to each person, and even the left eye is unique from the right eye. Compared with other biometric features (such face, voice, and etc), the iris is more stable and reliable. This paper proposes a new approach to iris recognition using 2D Log-Gabor spatial filters. Gabor filter has the disadvantage of DC component whenever the bandwidth is larger than one octave. The Log Gabor function removes the DC component. While the 1D Log-Gabor filter captures only the horizontal patterns, the 2D approach can capture the two dimensional characteristics of the iris patterns. Preliminary experimental results show that the proposed method has an encouraging performance.

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Identification of persons by means of the Fourier spectra of the optical transmission binary models of the human irises

Cited by 9 publications

References 3 publications

Iris Recognition Using Segmental Euclidean Distances

Iris Recognition Using Segmental Euclidean Distances

Personal Identification Based on Vectorcardiogram Derived from Limb Leads Electrocardiogram

Using 2D Log-Gabor spatial filters for iris recognition

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