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Finger-vein image enhancement using a fuzzy-based fusion method with Gabor and Retinex filtering.

Shin KY, Park YH, Nguyen DT, Park KR - Sensors (Basel) (2014)

Bottom Line: Our method is novel compared with previous approaches in four respects.Third, the optimal weights required to combine the two Gabor and Retinex filtered images are determined using a defuzzification method.Experimental results using two finger-vein databases showed that the proposed method enhanced the accuracy of finger-vein recognition compared with previous methods.

View Article: PubMed Central - PubMed

Affiliation: Division of Electronics and Electrical Engineering, Dongguk University, 26 Pil-dong 3-ga, Jung-gu, Seoul 100-715, Korea. skyandla@dongguk.edu.

ABSTRACT
Because of the advantages of finger-vein recognition systems such as live detection and usage as bio-cryptography systems, they can be used to authenticate individual people. However, images of finger-vein patterns are typically unclear because of light scattering by the skin, optical blurring, and motion blurring, which can degrade the performance of finger-vein recognition systems. In response to these issues, a new enhancement method for finger-vein images is proposed. Our method is novel compared with previous approaches in four respects. First, the local and global features of the vein lines of an input image are amplified using Gabor filters in four directions and Retinex filtering, respectively. Second, the means and standard deviations in the local windows of the images produced after Gabor and Retinex filtering are used as inputs for the fuzzy rule and fuzzy membership function, respectively. Third, the optimal weights required to combine the two Gabor and Retinex filtered images are determined using a defuzzification method. Fourth, the use of a fuzzy-based method means that image enhancement does not require additional training data to determine the optimal weights. Experimental results using two finger-vein databases showed that the proposed method enhanced the accuracy of finger-vein recognition compared with previous methods.

No MeSH data available.


Related in: MedlinePlus

Comparison of the outputs with Gabor and Retinex filtering using images from database II: (a) original image of the detected finger boundaries; (b) results with Gabor filtering; and results with Retinex filtering using sigma values of (c) 10, (d) 15, (e) 20, (f) 25, and (g) 50.
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f10-sensors-14-03095: Comparison of the outputs with Gabor and Retinex filtering using images from database II: (a) original image of the detected finger boundaries; (b) results with Gabor filtering; and results with Retinex filtering using sigma values of (c) 10, (d) 15, (e) 20, (f) 25, and (g) 50.

Mentions: The enhancement of thick vein lines is limited by the four-directional Gabor filter, whereas the thin vein lines become more distinct, as shown in Figures 9b and 10b. However, the thick vein lines are more distinct with Retinex filtering, as shown in Figures 9 and 10. Therefore, we can estimate that the local and global features of the vein lines are enhanced by the Gabor and Retinex filters, respectively. To enhance both the local and global features, we propose a fuzzy-based image fusion method for combining the Gabor and Retinex filtered images.


Finger-vein image enhancement using a fuzzy-based fusion method with Gabor and Retinex filtering.

Shin KY, Park YH, Nguyen DT, Park KR - Sensors (Basel) (2014)

Comparison of the outputs with Gabor and Retinex filtering using images from database II: (a) original image of the detected finger boundaries; (b) results with Gabor filtering; and results with Retinex filtering using sigma values of (c) 10, (d) 15, (e) 20, (f) 25, and (g) 50.
© Copyright Policy
Related In: Results  -  Collection

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Show All Figures
getmorefigures.php?uid=PMC3958271&req=5

f10-sensors-14-03095: Comparison of the outputs with Gabor and Retinex filtering using images from database II: (a) original image of the detected finger boundaries; (b) results with Gabor filtering; and results with Retinex filtering using sigma values of (c) 10, (d) 15, (e) 20, (f) 25, and (g) 50.
Mentions: The enhancement of thick vein lines is limited by the four-directional Gabor filter, whereas the thin vein lines become more distinct, as shown in Figures 9b and 10b. However, the thick vein lines are more distinct with Retinex filtering, as shown in Figures 9 and 10. Therefore, we can estimate that the local and global features of the vein lines are enhanced by the Gabor and Retinex filters, respectively. To enhance both the local and global features, we propose a fuzzy-based image fusion method for combining the Gabor and Retinex filtered images.

Bottom Line: Our method is novel compared with previous approaches in four respects.Third, the optimal weights required to combine the two Gabor and Retinex filtered images are determined using a defuzzification method.Experimental results using two finger-vein databases showed that the proposed method enhanced the accuracy of finger-vein recognition compared with previous methods.

View Article: PubMed Central - PubMed

Affiliation: Division of Electronics and Electrical Engineering, Dongguk University, 26 Pil-dong 3-ga, Jung-gu, Seoul 100-715, Korea. skyandla@dongguk.edu.

ABSTRACT
Because of the advantages of finger-vein recognition systems such as live detection and usage as bio-cryptography systems, they can be used to authenticate individual people. However, images of finger-vein patterns are typically unclear because of light scattering by the skin, optical blurring, and motion blurring, which can degrade the performance of finger-vein recognition systems. In response to these issues, a new enhancement method for finger-vein images is proposed. Our method is novel compared with previous approaches in four respects. First, the local and global features of the vein lines of an input image are amplified using Gabor filters in four directions and Retinex filtering, respectively. Second, the means and standard deviations in the local windows of the images produced after Gabor and Retinex filtering are used as inputs for the fuzzy rule and fuzzy membership function, respectively. Third, the optimal weights required to combine the two Gabor and Retinex filtered images are determined using a defuzzification method. Fourth, the use of a fuzzy-based method means that image enhancement does not require additional training data to determine the optimal weights. Experimental results using two finger-vein databases showed that the proposed method enhanced the accuracy of finger-vein recognition compared with previous methods.

No MeSH data available.


Related in: MedlinePlus