Assessment Of Color Normalization Algorithms Under Various Illuminations
Amrutha D. Pai
Amrutha D. Pai, Department of Electronics & Communication Engineering, N.M.A.M. Institute of Technology, Nitte, India.
Manuscript received on 19 August 2019. | Revised Manuscript received on 05 September 2019. | Manuscript published on 30 September 2019. | PP: 225-228 | Volume-8 Issue-11, September 2019. | Retrieval Number: K12910981119/2019©BEIESP | DOI: 10.35940/ijitee.K1291.0981119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Contrast enrichment is an essential area in the field of digital image handling for human visual perception and computer vision. Digital images have become a part of our everyday life and imaging devices are everywhere, from higher end digital cameras to video cameras integrated in laptops or cell phones. Images of a scenery taken with a number of cameras will possess diverse values of color owing to the deviations in reproducing color through various devices. Humans are likely to neglect the illumination while adjudicating the appearance of an entity. However the same does not hold true for various image capturing devices where the same object will often look different under different illuminations. The goal of the computational color normalization is to account for the result of the illuminate. This paper aims at simulating and comparing few of the color normalization algorithms like Histogram Equalization, Gamma correction and White patch Retinex using MATLAB image processing toolbox and a few statistical parameters related to the processed image are found. The results indicated that the retinex algorithm performed better than the other algorithms and it could be a prospective area of research in the field of face recognition.
Keywords: Color normalization, Image processing, MATLAB, Histogram equalization
Scope of the Article: Image Processing and Pattern Recognition