Quality assessment of NIR finger vascular images for exposure parameter optimization. Michał Waluś 1 , Krzysztof Bernacki 2* , Adam Popowicz 3 1 Faculty of Automatic Control, Electronics and Computer Science, Silesian University of Technology, Akademicka 16, 44-100 Gliwice, Poland 2 Institute of Electronics, Faculty of Automatic Control and Computer Science of the Silesian University of Technology, Akademicka 16, 44-100 Gliwice, Poland 3 Institute of Automatic Control, Faculty of Automatic Control and Computer Science of the Silesian University of Technology, Akademicka 16, 44-100 Gliwice, Poland Abstract The measurement of image quality plays an important role in all acquisition systems. In many medical applications, such as in the presented Near Infrared (NIR) imaging of the finger vascular system, there is no possibility of comparing the system outcomes with a reference data set. As a solution for this problem, a range of available methods have been presented, which try to reflect or imitate subjective human operator assessment. In this paper, we present a review of such quality metrics and introduce a novel approach based on distance transformations. The proposed method was compared with the state-of-the-art metrics on NIR vascular system images obtained by our constructed acquisition device. By changing the intensity of the finger backlight and by examining intentionally blurred images, we proved that our approach was capable of providing most sensible quality outcomes, while the others turned out to be much less reliable. The proposed evaluation technique may also be employed in any other medical application, where the assessment of the image quality has a direct impact on the final diagnosis. Keywords: Biomedical image processing, Finger vascular system, Image quality, Image enhancement. Accepted on February 28, 2016 Introduction Finger vascular recognition has been met with growing interest in the last few years. The available devices for biometric sample acquisition (research prototypes as well as commercial solutions) are based on lighting the finger by light-emitting near-infrared diodes (NIR-LED) and capturing images depicting the vein and artery structures. These structures are subcutaneous, thus they cannot be observed by the naked eye. Recently, several research centers worldwide have proposed diverse investigations to use finger vascular patterns for biometric recognition [1-9]. The first suggestion to use the blood vessel network as a biometric characteristic was made more than a decade ago [10] since then, a large number of different techniques for finger vein image acquisition and its preprocessing for the purpose of quality enhancement have been developed. In contrast to the other human identification methods, which involve face characteristics or fingerprints, the NIR vascular system recognition is more robust against spoofing because it requires the subject to both be alive and give permission. Finger vascular imaging is also used in an increasing number of new medical applications and is an alternative method to widespread imagery techniques, such as thermography, Doppler laser [11], plethysmography [12] or capillaroscopy [13]. NIR imaging methods do not require ionizing radiation and have great potential for, e.g., diagnosis of articular cartilage pathology [14] or breast cancer diagnosis [15]. In contrast to X-ray techniques, it is not harmful to living tissues, thus it may be employed with no danger to the patients. The main requirement for the correctness of recognition or the accuracy of the medical diagnosis is the highest possible quality of the images. To make the imaging system efficient and reliable, several hardware parameters, such as the backlight intensity or the exposure time, have to be optimized in the initial stage of the acquisition process. The image quality metrics are the main coefficients that control these optimization procedures. In this paper, we compare several image quality evaluation methods, and we also present a novel approach based on distance transformations. Our algorithm allows for the Biomedical Research 2016; 27 (2): 383-391 ISSN 0970-938X www.biomedres.info Biomed Res- India 2016 Volume 27 Issue 2 383