Developing a Smart Multimodal Biometric Authentication System based on Hand Vein

Abstract

Because of the uniqueness and complication of hand vein patterns the hand vein authentication gives a great level of recognition accuracy. The hand vein patterns are inside the body so that it can be a challenging technique to forge. Moreover, the system is contactless and hygienic for operate in society regions. The contactless hand vein recognition technology comprises of image sensor and software technology. The user’s hand is hold under an infrared ray scanner to capture an image of hand. The illumination of the infrared beam is limited relying on the light round the sensor, and the sensor is capable of take the hand image in spite of the location and movement of the hand. Afterward, the software compares the decoded vein image with the enrolled images, though determining the location and alignment of the hand by a pattern matching technique. This research reports a novel multimodal biometric system employing intelligent technique to authenticate human by fusion of dorsal hand, palm and finger veins pattern alternately. By explains an image analysis technique to detect the region of interest (ROI) from hand vein image. Once detecting ROI, construct a series of preprocessing steps for eliminate the transformation and rotation of hand vein images presented in the data gathering procedure and decrease several data quantity devoid of missing any effective information this stage done by used canny edge detector, dilation filter and erosion filter. Next construct a series of preprocessing steps to improve the contrast among hand vein patterns and background using median filter, 2D Wiener filter, Applied Contrast Limited Adaptive Histogram Equalization (CLAHE) filter and Homomorphic filter. Once hand vein pattern extracted it managed to obtain the features to use them in matching stage. This study use