• Nuradlin Borhan School of Electrical and Electronic Engineering, Universiti Sains Malaysia Engineering Campus, 14300, Nibong Tebal, Penang, Malaysia
  • Azwati Azmin School of Electrical and Electronic Engineering, Universiti Sains Malaysia Engineering Campus, 14300, Nibong Tebal, Penang, Malaysia
  • Masaki Yamakita System and Control Engineering, Tokyo Institute of Technology, Tokyo, Japan
  • Wan Mohd Yusof Rahiman Wan Abdul Aziz Cluster of Smart Port and Logistic Technology (COSPALT), Universiti Sains Malaysia Engineering Campus, 14300, Nibong Tebal, Penang, Malaysia



Biological stains, Blue bandpass filter, HSV, Segmentation, Threshold.


The world are facing threats due to the spread of bacteria and viruses. Thus, a lot of researches are continuously exploring the topic of contaminants. One of the most significant ways to kill the contaminants are by sanitizing. Unfortunately, there is a lack of methods in detecting the contaminants for the sanitization to be performed efficiently. In this paper, we proposed the approach of detecting biological stains using the combination of HSV color segmentation, UVA light and also blue bandpass filter. Using color segmentation with the aid from UVA light, the fluorescent image of detected stains can be extracted. In addition, the blue bandpass filter can filter out the presence of background noises in order to increase the accuracy of the detection. A simple experiment was conducted in order to validate the developed algorithm.


J. M. Boyce, 2007 “Environmental contamination makes an important contribution to hospital infection,” Journal of Hospital Infection, 65(SUPPL. 2): 50–54, . doi: 10.1016/S0195-6701(07)60015-2.

J. A. Otter, S. Yezli, J. A. G. Salkeld, and G. L. French, 2013, “Evidence that contaminated surfaces contribute to the transmission of hospital pathogens and an overview of strategies to address contaminated surfaces in hospital settings,” American Journal of Infection Control, 41(5 SUPPL.): S6, doi: 10.1016/j.ajic.2012.12.004.

J. Inkinen et al., 2020, “Contamination detection by optical measurements in a real-life environment: A hospital case study,” Journal of Biophotonics. 13(1): 1–8, doi: 10.1002/jbio.201960069.

S. J. Dancer, 2004, “How do we assess hospital cleaning? A proposal for microbiological standards for surface hygiene in hospitals,” J. Hosp. Infect., 56(1): 10–15, doi:

C. Willis, R. Morley, J. Westbury, M. Greenwood, and A. Pallett, 2007 “Evaluation of ATP bioluminescence swabbing as a monitoring and training tool for effective hospital cleaning,” British Journal of Infection Control, 8(5): 17–21, , doi: 10.1177/1469044607083604.

C. Malegori et al., 2020, “Identification of invisible biological traces in forensic evidences by hyperspectral NIR imaging combined with chemometrics,” Talanta, 215(March): 120911, doi: 10.1016/j.talanta.2020.120911.

T. Schubert, S. Wenzel, R. Roscher, and C. Stachniss, 2016, “INVESTIGATION of LATENT TRACES USING INFRARED REFLECTANCE HYPERSPECTRAL IMAGING,” ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 3:n97–102, doi: 10.5194/isprs-annals-III-7-97-2016.

L. Karchewski, G. Armstrong, M. Lou Nicliolson, and D. Wilkinson, 2014, “Assessment of the leeds spectral vision system for detecting biological stains on fabrics,” Canadian Society of Forensic Science Journal. 47(3–4): 230–243, doi: 10.1080/00085030.2014.929859.

G. J. Edelman, T. G. van Leeuwen, and M. C. Aalders, 2015, “Visualization of Latent Blood Stains Using Visible Reflectance Hyperspectral Imaging and Chemometrics,” Journal of Forensic Sciences. 60(s1): S188–S192,. doi: 10.1111/1556-4029.12591.

S. Sivachandiran, 2015. “Image Segmentation,” International Journal of Science Technology & Engineering, 2(2): 186–188,

S. E. Shih and W. H. Tsai, 2014, “A convenient vision-based system for automatic detection of parking spaces in indoor parking lots using wide-angle cameras,” IEEE Transactions on Vehicular Technology .63(6): 2521–2532, doi: 10.1109/TVT.2013.2297331.

D. Hema and D. S. Kannan, 2019, “Interactive Color Image Segmentation using HSV Color Space,” Sci. Technol. J., 7(1): 37–41, doi: 10.22232/stj.2019.07.01.05.

A. H. Pratomo, W. Kaswidjanti, A. S. Nugroho, and S. Saifullah, 2021 “Parking detection system using background subtraction and hsv color segmentation,” IEEE Transactions on Vehicular Technology, 10(6): 3211–3219, , doi: 10.11591/eei.v10i6.3251.

D. Giuliani, 2022, “Metaheuristic Algorithms Applied to Color Image Segmentation on HSV Space,” Journal of Imaging, 8(1): doi: 10.3390/jimaging8010006.

B. Hdioud, M. El Haj Tirari, R. Oulad Haj Thami, and R. Faizi, 2018 “Detecting and shadows in the HSV color space using dynamic thresholds,” Bulletin of Electrical Engineering and Informatics, 7(1): 70–79, doi: 10.11591/eei.v7i1.893.

F. S. Hassan and A. Gutub, 2022, “Improving data hiding within colour images using hue component of HSV colour space,” CAAI Transactions on Intelligence Technology. 7(1): 56–68, doi: 10.1049/cit2.12053.

Midopt, “Blue Bandpass Filter.” (accessed Mar. 17, 2021).

M. El Baz, T. Zaki, and H. Douzi, 2020. “Red Color Segmentation based Traffic Signs Detection 1,” 11(5): 121–127,

Y. Ito, C. Premachandra, S. Sumathipala, H. W. H. Premachandra, and B. S. Sudantha, 2021, “Tactile Paving Detection by Dynamic Thresholding Based on HSV Space Analysis for Developing a Walking Support System,” IEEE Access, 9: 20358–20367, doi: 10.1109/ACCESS.2021.3055342.

Z. Yan, Y. Yu, and M. Shabaz, 2021, “Optimization Research on Deep Learning and Temporal Segmentation Algorithm of Video Shot in Basketball Games,” CAAI Transactions on Intelligence Technology,2021: 1-10. doi: 10.1155/2021/4674140.




How to Cite

Borhan, N. ., Azmin, A. ., Yamakita, M. ., & Wan Abdul Aziz, W. M. Y. R. . (2023). BIOLOGICAL STAIN DETECTION USING OPENCV WITH THE AID OF ULTRAVIOLET A (UVA) LIGHT. ASEAN Engineering Journal, 13(3), 65-70.