Color Transformation Method for Protanopia Vision Deficiency using Artificial Neural Network

Authors

  • N. H. N. A. Wahab Centre for Artificial Intelligence & Robotic (CAIRO), Department of Electrical Engineering, Universiti Teknologi Malaysia, 81310 Skudai, Johor, Malaysia.
  • F. S. Ismail Centre for Artificial Intelligence & Robotic (CAIRO), Department of Electrical Engineering, Universiti Teknologi Malaysia, 81310 Skudai, Johor, Malaysia.
  • M. A. A. Nawawi Centre for Artificial Intelligence & Robotic (CAIRO), Department of Electrical Engineering, Universiti Teknologi Malaysia, 81310 Skudai, Johor, Malaysia.

Keywords:

Artificial Neural Network, Image Processing, Color Transformation, Color Vision Deficiency

Abstract

The objective of this project is to improve the ability of color discrimination for Protanope, who does not naturally develop red color or long wavelength cones. Intelligent method using image processing with Artificial Neural Network (ANN) is proposed to improve the ability of color discrimination as well as adjusting the images and colors. The image is stimulated by converting RGB space to LMS (long, medium, short) color space based on cone response and then modifies the response of the deficient cones. The linear multiplication matrix is referred to CIE color matching functions. Then the ANN is setting up by using the input/output from matrix conversion. The transformation of RGB color contrast technique is used to enhance contrast between red and green, which in general is green pixels appear to be bluer. Based on the result, the objectives are successfully achieved, which the ANN gives the minimum computational time than conventional matrix conversion, which is 36% increment. The changes of the image drastically for both color blind and non-color blind viewer. The result shows that the reds become redder and greens become greener from the image before being adjusted.

References

B. L. Cole, Assessment of inherited color vision defects in clinical practice. Clin Exp Optom, vol. 90, no.3, pp. 157-75, 2007.

Jacek Rumiski, Jerzy Wtorek, Joanna Rumiska, “Color Transformation Methods for Dichromats,” in Human System Interaction (HSI), 3rd IEEE International Conference. 2010.

T. Ohkubo, K. Kobayashi, “A color compensation vision system for color-blind people,” in SICE Annual Conference. 2008.

S. Poret, R. D. Dany, “Image Processing for Color Blindness Correction,” in Science and Technology for Humanity (TIC-STH), Toronto International Conference IEEE. 2009, pp. 539-544.

Dabhoiwala, Mazgaonkar, Tole, “An Overview on Various Re-Coloring Methods for The Color Vision Deficient,” International Journal of Advance Foundation And Research in Science & Engineering (IJAFRSE), vol. 1, no.11, pp. 5-15, 2015.

Jeong Jae-Yun, Kim Hyun-Ji, Wang Tae-Shick, Ko Sung-jea, “An Efficient Recoloring Method with Information Preserving for the Color-blind,” IEEE Transactions on Consumer Electronics, 57, no. 4, pp. 1953-1960, 2011.

J. Ruminski, M. Bajorek, J. Ruminska, J. Wtorek, A. Bujnowski, “Computerized Colour Processing for Dichromats,” Human – Computer Systems Interaction, AISC 98, pp. 453-470, 1998.

J. P. Srividhya, P. Sivakumar, M. Rajaram, “The Color Blindness Removal Technique In Image by Using Gradient Map Method,” in 2011 International Conference on Signal Processing, Communication, Computing and Networking Technologies (ICSCCN), 2011.

S. Sapnal, Dr. A. Tamilarasi, M. Pravin Kumar, “Backpropagation Learning Algorithm Based on Levenberg Marquardt Algorithm,” Computer Science & Information Technology, pp. 393-398, 2012.

M. Egmont-Peterson, D. de Ridder, H. Handels, “Image processing With Neural Networks – A Review,” 2002 Elsevier Science, vol. 35, no. 10, pp. 2279-2301, 2002.

C. A. Curcio, K. R. Sloan, R. E. Kalina, A. E. Hendrickson, “Human photoreceptor Topography,” J Comp Neurol, vol. 292, pp. 2279-2301, 2002.

N. Sutender, “Study of colour blindness in Jat Sikhs,” Indian J Physiol Pharmacol, vol. 39, pp. 127-130, 1995.

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Published

2016-12-01

How to Cite

A. Wahab, N. H. N., Ismail, F. S., & A. Nawawi, M. A. (2016). Color Transformation Method for Protanopia Vision Deficiency using Artificial Neural Network. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 8(11), 29–33. Retrieved from https://jtec.utem.edu.my/jtec/article/view/1406