Separable Gabor filter realization for fast fingerprint enhancement

Areekul, Vutipong; Watchareeruetai, Ukrit; Suppasriwasuseth, K.; Tantaratana, S.

doi:10.1109/icip.2005.1530376

Cited by 45 publications

(19 citation statements)

References 6 publications

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“…In the study of Deng et al [10], has defined a scheme of facial identify that based on the principal of Gabor-filter for feature extraction. To extract the features it consist eight orientation and five frequencies.…”

Section: Literatur Esurveymentioning

confidence: 99%

Development and Implementation of VLSI Reconfigurable Architecture for Gabor Filter in Medical Imaging Application

Hegde¹,

Sivakumar²

2018

IJEMR

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The Gabor filter is a very effective tool in visual search approaches and multimedia applications. This filter provides high resolution in time-frequency domains and thus finds use in object recognition, character recognition and pattern recognition applications. Medical Image analysis using image processing algorithms is one of the best ways of diagnosing diseases inside human body. The Gabor wavelets resemble the visual cortex cell operation of mammalian brains and hence are best suited for biological image analysis. A Tonsillitis detection system is proposed here using Gabor filtering approach. This system detects the presence of Tonsillitis from the tonsils images. A suitable VLSI architecture for the implementation of the Gabor filter was modeled in Verilog using Xilinx tool and simulated using the tonsils test images. The proposed system was successful in detecting the presence of Tonsillitis from the diseased tonsils image. The complete system was then synthesized and implemented on FPGA Artix 7. The design was capable of operating at a maximum frequency of 394.563 MHz.

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Section: Literatur Esurveymentioning

confidence: 99%

Development and Implementation of VLSI Reconfigurable Architecture for Gabor Filter in Medical Imaging Application

Hegde¹,

Sivakumar²

2018

IJEMR

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“…However, with low quality fingerprint, the highest peak could not pinpoint. [4], (c) Enhanced results from STFT approach modified from [5] in frequency domain, (d) Enhanced results from DCT approach method [6] in frequency domain…”

Section: Fingerprint Enhancement Problemsmentioning

confidence: 99%

“…The fingerprint image is partitioned into blocks of 16×16 pixels, and a basic segmentation scheme using mean and variance is employed. Five fingerprint enhancement filtering types are evaluated as follows; Traditional Gabor filtering with non-quantized orientation (TG) [2], Separable Gabor filtering with 8-quantized orientation (SG8) [3], Separable Gabor filtering with non-quantized orientation (SG) [4], Short Time Fourier Transform approach (STFT) [5], and Discrete Cosine Transform approach (DCT) [6]. In the spatial domain approaches, the discrete Gabor filters are the same 25×25 fixed-window size.…”

Section: Step 1) Initial Sequence Alignmentmentioning

confidence: 99%

“…This method employs a set of pre-computed Gabor filters that selected by local ridge orientation and local ridge frequency in order to perform 2-D convolution with an entire image. In addition, computational complexity of this Gabor filtering can be reduced by applying separable Gabor filters as reported in [3,4]. In frequency-domain approaches, Gabor filter can be implemented in Short Time Fourier Transform (STFT) domain, resulting in better enhancement around high curvature zone [5].…”

Section: Introductionmentioning

confidence: 99%

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Performance and Computational Complexity Comparison of Block-Based Fingerprint Enhancement

Jirachaweng

Leelasawassuk

Areekul

2009

Advances in Biometrics

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Abstract. Performance and computational complexity comparisons of various block-based fingerprint enhancement schemes are tested and reported in this literature. Enhancement performance is evaluated by comparing equal error rates, which obtained by a proposed fingerprint matching algorithm using local and global features. Various enhancement methods are tested; i.e. three types of spatial Gabor filtering, short-time Fourier transform filtering, and discrete cosine transform filtering. These enhancement schemes also tested with various databases such as FVC2000, FVC2002, and FVC2004. Finally, computational complexity of enhancement implementation is analyzed and concluded.

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“…Usually dedicated enhancement algorithms are time consuming applications. Most of fingerprint image enhancement approaches are based on Gabor filter [17] [18]. The Gabor approach is a frequency-selective and orientation-selective filter tuned by ridge directions and ridge frequencies in fingerprint.…”

mentioning

confidence: 99%

Morphological Enhancement and Triangular Matching for Fingerprint Recognition

Conti¹,

Milici²,

Vitabile³

et al.

Innovations and Advanced Techniques in Systems, Computing Sciences and Software Engineering

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Abstract. Among the principal problems for realizing a robust Automated Fingerprint Identification System (AFIS) there are the images quality and matching algorithms. In this paper a fingerprint enhancement algorithm based on morphological filter and a triangular matching are introduced. The enhancement phase is based on tree steps: directional decomposition, morphological filter and composition. For the matching phase a global transformation to overcame the effects of rotation, displacement and deformation between acquired and stored fingerprint is performed using the number of similar triangular, having fingerprint minutiae as vertexes. The performance of the proposed approach has been evaluated on two set of images: the first one is DB3 database from Fingerprint Verification Competition (FVC) and the second one is self collected using an optical scanner. I. INTRODUCTIONAn Automated Fingerprint Identification System (AFIS) can work in two different ways [6] [7]:• Verification mode: the on-line biological signature is compared with the registered signature. With more details, a username is used to select the database item and perform a 1 -> 1 match.• Identification mode: the on-line biological signature is compared with the registered signatures. With more details 1 -> n matches must be performed in order to select the candidate with the highest matching score. Fingerprint are composed by a unique pattern of locally parallel ridge and valley with well defined orientation. To compare fingerprints in an Automatic Fingerprint Identification System (AFIS), local ridge structure characteristics, called minutiae, are usually used. The minutiae used in an AFIS are ridge ending and ridge bifurcation.Generally, the AFIS performance depends by image quality. The ridge-valley structures are rather well visible in a poor quality fingerprint image because a wrong fingerprint impression produces imperfections, genuine features alteration and many false features introduction.In addition, an incorrect image acquisition due to a wrong finger displacement produces partial fingerprint acquisition, roto-translation displacements and non linear deformation.In this paper, a directional morphological filter, in image enhancement process for improving the clarity of ridge/valley structures, is applied. In addiction, an enhanced matching algorithm with respect to [14], has been used to overcame the effects of rotation, displacement and deformation between acquired and stored fingerprint. The matching score is related to the number of similar triangular, having fingerprint minutia as vertexes, in the acquired and the stored images.In literature different approaches for fingerprint image enhancement were proposed [19][20]. Usually dedicated enhancement algorithms are time consuming applications. Most of fingerprint image enhancement approaches are based on Gabor filter [17] [18]. The Gabor approach is a frequency-selective and orientation-selective filter tuned by ridge directions and ridge frequencies in fingerprint. It works both on spa...

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Separable Gabor filter realization for fast fingerprint enhancement

Cited by 45 publications

References 6 publications

Development and Implementation of VLSI Reconfigurable Architecture for Gabor Filter in Medical Imaging Application

Development and Implementation of VLSI Reconfigurable Architecture for Gabor Filter in Medical Imaging Application

Performance and Computational Complexity Comparison of Block-Based Fingerprint Enhancement

Morphological Enhancement and Triangular Matching for Fingerprint Recognition

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