Adaptive Learning Gabor Filter for Finger-Vein Recognition

Zhang, Yakun; Li, Weijun; Zhang, Liping; Ning, Xin; Sun, Linjun; Lu, Yaxuan

doi:10.1109/access.2019.2950698

Cited by 75 publications

(29 citation statements)

References 53 publications

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“…Two-dimensional Gabor filter is very sensitive to the texture edge of the image and its expression of frequency and orientation is consistent with the texture recognition mechanism of the human vision system [25]. Gabor filter can effectively enhance the edge, peak, valley, ridge contours and other underlying feature information.…”

Section: Vertical Phase Difference Coding Methods Based On Gabor Filtermentioning

confidence: 61%

Finger Vein Image Inpainting With Gabor Texture Constraints

et al. 2020

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The texture edge continuity of a finger vein image is very important for the accuracy of feature extraction. However, the traditional inpainting methods which, without accurate texture constraints, are easy to cause the vein texture of the inpainted image to be blurred and break. A finger vein image inpainting method with Gabor texture constraints is proposed. The proposed method effectively protects the texture edge continuity of the inpainted image. Firstly, using the proposed vertical phase difference coding method, the Gabor texture feature matrix of the finger vein image, which can accurately describe the texture information, can be extracted from the Gabor filtering responses. Then, according to the local texture continuity of the finger vein image, the known pixels, which have different texture orientations with the center pixel in the patch, are filtered out using the Gabor texture constraining mechanism during the inpainting process. The proposed method eliminates irrelevant information interference in the inpainting process and has a more precise texture propagation. Simulation experiments of artificially synthetic images and acquired images show that the finger vein images inpainted by the proposed method have better texture continuity and higher image quality than the traditional methods which do not have accurate texture constraints. The proposed method improves the recognition performance of the finger vein identification system with the acquired damaged images.INDEX TERMS Finger vein image, Gabor filter, image inpainting, texture feature, vertical phase difference coding.HUAXIA WANG (Member, IEEE) received the B.Eng. degree in information engineering from

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Section: Vertical Phase Difference Coding Methods Based On Gabor Filtermentioning

confidence: 61%

Finger Vein Image Inpainting With Gabor Texture Constraints

et al. 2020

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“…The results showed the effectiveness of the proposed method and outperformed the previous methods in both integrity and positional accuracy of the residential boundary. Zhang et al [43] combined the convolutional neural networks with a Gabor filter to calculate the gradient of the Gabor filter parameters. The calculation was based on the objective function, then the parameter optimization was performed via back-propagation.…”

Section: Related Workmentioning

confidence: 99%

Fuzzified Circular Gabor Filter for Circular and Near-Circular Object Detection

et al. 2020

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This paper presents a new algorithm for filtering and detecting circular and deformed circular objects. The resulting procedure is based on fuzzifying the parameters of a circular Gabor filter to optimize the response of the circular Gabor filter and achieve additional selectivity of the filter. Circular and deformed circular objects of interest were efficiently extracted, and considerable resistance to noise and image degradation was achieved. INDEX TERMS Circular Gabor filters, fuzzification of filter parameters, fuzzy system, image filtering, image texture analysis, object detection.

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“…In image processing, they are used for feature extraction, edge detection, texture analysis, etc. The Gabor function has the capability to capture the localized information with respect to spatial frequency, location, and selection of direction [20]. Mathematically Gabor filters [21,22]are expressed as a function: 2) Apply Gabor Filters: Three images are selected to form two pairs of images, where one image is common to both.…”

Section: B Workingmentioning

confidence: 99%