A novel fuzzy curvature method for recognition of anterior forearm subcutaneous veins by thermal imaging

Anterior forearm recognition systems emerged in last decades to identify the vein systems and to decide the venipuncture sites. Basically, identification and also real-time visualization of the forearm veins are commonly accomplished by near-infrared (NIR) camera systems in the literature and also in applied medicine; however what we propose in this paper is easier and reliable alternative by thermal imaging. While identifying vein systems, the common drawback of visible spectrum and NIR camera solutions is lack of recognition possibility of rather hidden veins in the forearms. In other words, while these solutions are so useful for identification of superficial veins like Median Cubital and Median Antebrachial veins; yet they are not so efficient for subcutaneous veins like Cephalic vein. Therefore, we introduce a novel fuzzy directional curvature methodology to recognize the whole vein system of anterior forearm using infrared thermal (IR-T) imaging. Initially, the forearm image captured by a thermal camera is segmented by crisp 2-means and filtered by Gaussian high-pass filter for smoothing and contrast enhancement. Four types of directional curvatures, achieved by second order derivatives including vertical, horizontal and two diagonal directions, are reproduced as four single images from scratch. The images are subsequently fused by fuzzy curvature method to produce the final images representing the complete vein system in the forearm. The fusion procedure by fuzzy inference system as an expert system could be stated as the main novelty in infrared thermal imaging which is also so flexible thanks to the parametric design. The intelligent recognition system also provides various clear screenings of the whole vein system in forearms depending on the parameters selected, even though the veins are totally invisible. (C) 2018 Elsevier Ltd. All rights reserved.