Limits...
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

Enhanced images obtained using the proposed method with four-directional Gabor filtering and Retinex filtering with a sigma value of 15 using images from database II: (a) Gabor filtered image; (b) Retinex filtered image with a sigma value of 15; and (c) Fuzzy FOM based on the Max rule.
© Copyright Policy
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC3958271&req=5

f24-sensors-14-03095: Enhanced images obtained using the proposed method with four-directional Gabor filtering and Retinex filtering with a sigma value of 15 using images from database II: (a) Gabor filtered image; (b) Retinex filtered image with a sigma value of 15; and (c) Fuzzy FOM based on the Max rule.

Mentions: To demonstrate the increased recognition accuracy with the proposed method regardless of the type of database used, additional experiments were conducted with images from database II. Figure 24 shows the images produced with the proposed method using Gabor filtered images and Retinex filtered images with sigma values of 15 for images from database II.


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)

Enhanced images obtained using the proposed method with four-directional Gabor filtering and Retinex filtering with a sigma value of 15 using images from database II: (a) Gabor filtered image; (b) Retinex filtered image with a sigma value of 15; and (c) Fuzzy FOM based on the Max rule.
© Copyright Policy
Related In: Results  -  Collection

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

f24-sensors-14-03095: Enhanced images obtained using the proposed method with four-directional Gabor filtering and Retinex filtering with a sigma value of 15 using images from database II: (a) Gabor filtered image; (b) Retinex filtered image with a sigma value of 15; and (c) Fuzzy FOM based on the Max rule.
Mentions: To demonstrate the increased recognition accuracy with the proposed method regardless of the type of database used, additional experiments were conducted with images from database II. Figure 24 shows the images produced with the proposed method using Gabor filtered images and Retinex filtered images with sigma values of 15 for images from database II.

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