Multi-Distance Veins Projection Based on Single Axis Camera and Projector System

  • I Putu Adi Surya Gunawan Politeknik Elektronika Negeri Surabaya, Indonesia
  • Riyanto Sigit Politeknik Elektronika Negeri Surabaya, Indonesia
  • Agus Indra Gunawan Politeknik Elektronika Negeri Surabaya, Indonesia
Keywords: veins, back-projection, ultrasonic distance sensor

Abstract

Every person has different location of veins, some veins are easily detected because it is visible due to thin tissue, and the other are invisible. This different location of veins causes intravenous access procedures and the procreas of intravenous therapy become longer. Multi-distance vein projections aim to simplify the measurement process where the device and object do not have to be at a certain distance. Some research that has been done especially for real-time vein projection does not conduct how the characteristics of projection at different distances. In this paper, we propose a method for performing multi-distance real-time back-projection by using the intersection between camera and projector. This method equiped with an ultrasonic distance sensor to identify the projection characteristic in any distance. In its implementation, this method is able to project at a distance of 20-40 cm with a maximum projection error of 0.6 mm. The measurement angle tolerance between the object and the device is ±5 degrees with a maximum error of 0.7 mm.

Downloads

Download data is not yet available.

Author Biography

I Putu Adi Surya Gunawan, Politeknik Elektronika Negeri Surabaya, Indonesia

Electrical Engineering

References

Min Joung Kim et al., Efficacy of VeinViewer in pediatric peripheral intravenous access: A randomized controlled trial, Eur. J. Pediatr., vol. 171, no. 7, pp. 1121–1125, 2012.

Simon Juric and Borut Zalik, An innovative approach to near-infrared spectroscopy using a standard mobile device and its clinical application in the real-time visualization of peripheral veins, BMC Med. Inform. Decis. Mak., vol. 14, no. 1, pp. 1–9, 2014. DOI: https://doi.org/10.1186/s12911-014-0100-z

Herbert D. Zeman, Prototype vein contrast enhancer, Opt. Eng., vol. 44, no. 8, p. 086401, 2005.

Xaobin Dai, Ya Zhou, Xiaoming Hu, Meiqing Liu, Xia Zhu, and Zhaogou Wu, A fast vein display device based on the camera-projector system, IST 2013 - 2013 IEEE Int. Conf. Imaging Syst. Tech. Proc., pp. 146–149, 2013.

D. Ai et al., Augmented reality based real-time subcutaneous vein imaging system, Biomed. Opt. Express, vol. 7, no. 7, p. 2565, 2016. DOI: https://doi.org/10.1364/BOE.7.002565

I Putu Adi Surya Gunawan, Riyanto Sigit, and Agus Indra Gunawan, Vein Visualization System Using Camera and Projector Based on Distance Sensor, in 2018 International Electronics Symposium on Engineering Technology and Applications (IES-ETA), 2018, pp. 150–156. DOI: https://doi.org/10.1109/ELECSYM.2018.8615501

Scott Prahl, Optical Arbsorption of Hemoglobin, 1999. [Online]. Available: https://omlc.org/spectra/hemoglobin/. [Accessed: 21-Jan-2018].

Donghoon Kim, Yujin Kim, Siyeop Yoon, and Deukhee Lee, Preliminary study for designing a novel vein-visualizing device, Sensors (Switzerland), vol. 17, no. 2, 2017. DOI: https://doi.org/10.3390/s17020304

Liukui Chen, Jing Wang, Shiyu Yang, and Haibo He, A Finger Vein Image-Based Personal Identification System with Self-Adaptive Illuminance Control, IEEE Trans. Instrum. Meas., vol. 66, no. 2, pp. 294–304, 2017. DOI: https://doi.org/10.1109/TIM.2016.2622860

Yiding Wang, Yun Fan, Weiping Liao, Kafeng Li, Lik-Kwan Shark, and Martin R. Varley, Hand vein recognition based on multiple keypoints sets, Proc. - 2012 5th IAPR Int. Conf. Biometrics, ICB 2012, pp. 367–371, 2012. DOI: https://doi.org/10.1109/ICB.2012.6199778

Anagha. B. Bawase and P. S. D. Apte, Infrared Hand Vein Detection System, pp. 48–52, 2015.

Adam Shidqul Aziz, Riyanto Sigit, Achmad Basuki, and Taufik Hidayat, Cardiac Motions Classification on Sequential PSAX Echocardiogram, Indones. J. Electr. Eng. Comput. Sci., vol. 12, no. 3, pp. 1289–1296, 2018.

Galih Hendra Wibowo, Riyanto Sigit, and Ali Ridho. Barakbah, Javanese Character Feature Extraction Based on Shape Energy, EMITTER International Journal Engineering Technology, vol. 5, no. 1, pp. 154–170, 2017. DOI: https://doi.org/10.24003/emitter.v5i1.175

Muqing Zhou, Zhaogou Wu, Difan Chen, and Ya Zhou, An improved vein image segmentation algorithm based on SLIC and Niblack threshold method, Proc. SPIE 9045, 2013 Int. Conf. Opt. Instruments Technol. Optoelectron. Imaging Process. Technol., vol. 9045, p. 90450D, 2013.

George. J. Tserevelakis et al., Photoacoustic imaging reveals hidden underdrawings in paintings, Sci. Rep., vol. 7, no. 1, pp. 1–11, 2017. DOI: https://doi.org/10.1038/s41598-017-00873-7

Rebecca. Sharp et al., Measurement of Vein Diameter for Peripherally Inserted Central Catheter (PICC) Insertion: An Observational Study, J. Infus. Nurs., vol. 38, no. 5, pp. 351–357, 2015. DOI: https://doi.org/10.1097/NAN.0000000000000125

Published
2019-12-01
How to Cite
Gunawan, I. P. A. S., Sigit, R., & Gunawan, A. I. (2019). Multi-Distance Veins Projection Based on Single Axis Camera and Projector System. EMITTER International Journal of Engineering Technology, 7(2), 444-466. https://doi.org/10.24003/emitter.v7i2.367
Section
Articles