Volume XLII-2/W4
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W4, 193–197, 2017
https://doi.org/10.5194/isprs-archives-XLII-2-W4-193-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W4, 193–197, 2017
https://doi.org/10.5194/isprs-archives-XLII-2-W4-193-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

  10 May 2017

10 May 2017

INFRARED CEPHALIC-VEIN TO ASSIST BLOOD EXTRACTION TASKS: AUTOMATIC PROJECTION AND RECOGNITION

S. Lagüela1,2, M. Gesto2, B. Riveiro1, and D. González-Aguilera2 S. Lagüela et al.
  • 1Applied Geotechnologies Research Group, University of Vigo, 36310 Vigo, Spain
  • 2Dept. of Cartographic and Terrain Engineering, University of Salamanca, 05001 Ávila, Spain

Keywords: infrared thermography; projector; pattern recognition; cephalic vein; thermal map

Abstract. Thermal infrared band is not commonly used in photogrammetric and computer vision algorithms, mainly due to the low spatial resolution of this type of imagery. However, this band captures sub-superficial information, increasing the capabilities of visible bands regarding applications. This fact is especially important in biomedicine and biometrics, allowing the geometric characterization of interior organs and pathologies with photogrammetric principles, as well as the automatic identification and labelling using computer vision algorithms.

This paper presents advances of close-range photogrammetry and computer vision applied to thermal infrared imagery, with the final application of Augmented Reality in order to widen its application in the biomedical field. In this case, the thermal infrared image of the arm is acquired and simultaneously projected on the arm, together with the identification label of the cephalic-vein. This way, blood analysts are assisted in finding the vein for blood extraction, especially in those cases where the identification by the human eye is a complex task. Vein recognition is performed based on the Gaussian temperature distribution in the area of the vein, while the calibration between projector and thermographic camera is developed through feature extraction and pattern recognition. The method is validated through its application to a set of volunteers, with different ages and genres, in such way that different conditions of body temperature and vein depth are covered for the applicability and reproducibility of the method.