Abstract
A novel infrared finger vein biometric identification is proposed using Linear Gabor filter with Guidance image and SIFT feature matching. Linear Gabor filter with guidance image is used for extracting finger vein pattern without segmentation processing and also performs well with some poor quality images due to low contrast, illuminance imbalance or noise etc. Firstly, we utilized Guided Linear Gabor filter for ridge detection as simple Linear Gabor filter and also enhance the image by performing edge preserving smoothing operation. Secondly we utilized SIFT feature matching for verification. A SIFT (Scale Invariant Feature Transform) can extract features to posses rotation invariance and shift invariance for providing better matching rate. The simulation analysis shows our proposed system is an effective feature for finger vein biometric identification.
Highlights
Finger vein based personal identification [1] [2] is most effective in biometric identification
Linear Gabor filter with guidance image is used for extracting finger vein pattern without segmentation processing and performs well with some poor quality images due to low contrast, illuminance imbalance or noise etc
Various Texture feature extraction techniques based on statistical, structural, model based and transform method are available in literature [5] [6]
Summary
Finger vein based personal identification [1] [2] is most effective in biometric identification. Various Texture feature extraction techniques based on statistical, structural, model based and transform method are available in literature [5] [6]. Analyse the finger vein pattern characteristics are carried out decomposing the image in to frequency domain components [5] [6]. Linear Gabor filter able to capture texture features at different orientation and frequency. Linear Gabor filter [6] – [11] significantly extracts the texture features compare to other methods. The guidance image of Dennis Linear Gabor filter is to extract the properties of finger vein pattern and reduce the background illumination, haze and the blood flow noise. After successful feature extraction of finger vein image pattern we need to concentrate on image registration for verification. SIFT based image registration and matching is utilized for authentication
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