Technique Study Of Palm Vein Image Recognition

Human palm vein is a permanent and unique physiological feature for biometric. Ithides under the skin and its distribution is hard to copy; it can be captured under nearinfrared but can’t be captured under visiable light; palm vein can be captured as peoplehold hand flat while the nature condition of hand is half clenched fists state, which makespalm vein image difficult for candid shooting. Palm vein in broken palm or dead bodycan’t be used for identification for no blood flow. For this reason, palm vein can be usedfor a “liveness detection” physiological feature for biometric. All these characters makepalm vein a high security physiological feature for biometric. As a leading subject ofbiometrics technology, palm vein image recognition has a wide prospect of application forits outstanding characters, such as high security. Palm vein image recognition has alreadybeen a new research focus in recent years.At present, study of palm vein recognition is on the stage of experiment. Manyproblems need tobe solved to develop real rubost and practical system. This paper doessome work as follows:To the question of which band is the best for an active light in the recognition system,this paper does choice in the typical wavelength of palm vein recognition:760nm,850nm,890nm and940nm. This study solves this problem from two angles. From the angle offeature extraction, establish a model of palm vein image definition and do the choice of thefour kinds of wavelength according to the model. From the angle of feature matching,compare the recognition performance of palm vein image with four kinds of wavelengthseparately by three typical biological identification algorithms. The experiment results ofthe model and3algorithms show that850nm is the optimal wavelength.Traditional palm vein recognition systems use the center of palm as region ofinteresting (ROI), which is troubled with fuzziness of palm vein on palm center area.Consequently, the fuzziness influences the performance of the system. This paper doessome study on the selection and location of ROI. It does medical analysis and contrast experiment of light absorption on the three areas of the palm: the center area, the thenararea and the hypothenar area. The thenar area is selected as the main scope of ROI.According to this result, this paper proposes a location method based on the thenar area.The method finds two stable characteristic points and squares the ROI with these twopoints.To the secrity question of contact palm vein recognition system, an algorithm basedon blocking and grayscale surface matching is proposed. The algorithm extracts region ofinteresting (ROI) of palm vein image firstly. Then, the ROI is equally divided into severalsub-regions. The algorithm computes the average value of the grayscale of everysub-region. These average values construct an image for matching. At the stage ofmatching, the algorithm computes the difference of the corresponding pixels from twomatching images and gets the grayscale difference surface. It calculates the variance of thegrayscale difference surface and considers this variance as the distance between twofeature surfaces. At last, it decides whether these two images come from the same hand ornot according to the variance. The experiment results show that the method is fast andproposes a way of high safety.Low restriction of contactless palm vein collection may cause image deformation andintra-class different increase, which consequently influence the performance of the system.This paper proposes an algorithm of contactless palm vein recognition based on blockingand partial least squares. The algorithm of image block is used to rapidly reduce thedimension firstly. At the same time, the algorithm of image block can settle image rotationand translation in some degree. Then, the algorithm of partial least squares is used toextract some directions with sharp grayscale variation and omits some directions withweak grayscale variation. The extractived components have the maximum relationshipwith the classical information. The algorithm makes the samples overcome the imagerotation, translation, scale and illumination change in intra-class in the maximum limit. Itprojects to the subspace which is the most beneficial to classification and gets the stablecharacter vectors. The algorithm of partial least squares reduces dimensions at the sametime. At last, Euclidean distance is used for classification. The experiment results showthat compared with the traditional method, the proposed method increases the CorrectRecognition Rate (CRR) and decreases the false rejection rate (FRR).