Application of GWO-BP Neural Network in Color Correction of Tongue Diagnosis Images
Objective:Based on the Grey Wolf Optimization(GWO)algorithm,to optimize the tongue diagnosis image color correction algorithm of the traditional BP neural network,and to solve the problems such as the limitation of shooting environment of mobile tongue diagnosis APP and the dependence of mobile phone devices and the poor effect of traditional algorithm used by color correction method based on mobile phone platform.Methods:Using 24-color standard color card as the standard,the tongue diagnosis images of indoor incandescent lamp under different light intensity and outdoor cloudy and sunny scenes at different times were collected.At the same time,grayscale world algorithm and traditional BP neural network algorithm were selected to compare with the proposed algorithm of this paper.The above three algorithms were used to correct the color of the acquired image,and the correction results were compared with objective and subjective color evaluation.Results:Compared with gray-scale world algorithm and BP neural network algorithm,the color correction effect of GWO-BP neural network algorithm was significantly improved.Conclusion:The GWO-BP algorithm can effectively correct the color of tongue diagnosis images taken by mobile phones,so as to improve the accuracy of color values.
Tongue diagnosis imagesColor calibrationGrey Wolf Optimization algorithmBP neural network
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