Non-Invasive Anemia Screening Using Nails and Palms Photos


  • Mangaras Yanu Florestiyanto Universitas Pembangunan Nasional Veteran Yogyakarta
  • Nandha Juniaroesita Peksi Universitas Pembangunan Nasional Veteran Yogyakarta



anemia, image processing, classification, Naïve Bayes


Anemia is a condition where the hemoglobin level is below standard. Hemoglobin is an iron-rich protein that gives blood its red color and is tasked with helping red blood cells carry oxygen from the lungs throughout the body, including essential body organs such as the heart, kidneys, and other organs. So that if anemia is allowed to drag on, it will interfere with the function of these organs and cause various kinds of diseases.This study applies the Naive Bayes method to detect anemia using digital images of the nails and palms as parameters. The image processing method used in this research is image segmentation in digital images of nails and palms so that they are separated from the background using the threshold method, after which the mean values of Red, Green, Blue, and their standard deviation are found. Furthermore, the value obtained will be processed using the Naïve Bayes classification method to categorize the palm image data entered into the anemia or non-anemia category. The proposed method achieves 90 percent accuracy for the paleness classification of nails and palms pictures. The proposed paleness screening method can be further fine-tuned to identify the intensity of anemia-like pathologies by using a controlled collection of local images that can then be used for potential benchmarking purposes.


Aparna, V., Sarath, T. V. and Ramachandran, K. I. (2017) 'Simulation model for anemia detection using RBC counting algorithms and Watershed transform,' 2017 International Conference on Intelligent Computing, Instrumentation and Control Technologies, ICICICT 2017, pp. 284–291. DOI: 10.1109/ICICICT1.2017.8342575.

Chen, Y. M., Miaou, S. G. and Bian, H. (2016) 'Examining palpebral conjunctiva for anemia assessment with image processing methods,' Computer Methods and Programs in Biomedicine. Elsevier Ireland Ltd, 137, pp. 125–135. DOI: 10.1016/j.cmpb.2016.08.025.

Dimauro, G. et al. (2018) 'Automatic Segmentation of Relevant Sections of the Conjunctiva for Non-Invasive Anemia Detection,' 2018 3rd International Conference on Smart and Sustainable Technologies, SpliTech 2018. University of Split, FESB, pp. 1–5.

Duke, W. W. (1928) 'Palm Color Test : A Simple, Practical Clinical Method For The Diagnosis of Anemia and Plethora', Archive of Internal Medicine, 42(4), pp. 533–545.

Sanchez-Carrillo, C. I. et al. (1989) 'Test of a non-invasive instrument for measuring hemoglobin concentration,' International Journal of Technology Assessment in Health Care, 5(4), pp. 659–667. DOI: 10.1017/S0266462300008527.

Sheth, T. N. et al. (1997) 'The relation of conjunctival pallor to the presence of anemia,' Journal of General Internal Medicine, 12(2), pp. 102–106. DOI: 10.1046/j.1525-1497.1997.00014.x.

Suner, S. et al. (2007) 'Non-Invasive Determination of Hemoglobin by Digital Photography of Palpebral Conjunctiva', Journal of Emergency Medicine, 33(2), pp. 105–111. DOI: 10.1016/j.jemermed.2007.02.011.

Tamir, A. et al. (2018) 'Detection of anemia from the image of the anterior conjunctiva of the eye by image processing and thresholding,' 5th IEEE Region 10 Humanitarian Technology Conference 2017, R10-HTC 2017, 2018-Janua, pp. 697–701. DOI: 10.1109/R10-HTC.2017.8289053.

WHO (2012) 'Anaemia Policy Brief,' (6), pp. 1–7. Available at:

Yalçin, S. S. et al. (2007) 'The validity of pallor as a clinical sign of anemia in cases with beta-thalassemia,' Turkish Journal of Pediatrics, 49(4), pp. 408–412.

Zucker, J. R. et al. (1997) 'Clinical signs for the recognition of children with moderate or severe anemia in western Kenya,' Bulletin of the World Health Organization, 75(SUPPL. 1), pp. 97–102.