In this study, colorimetric calibration of scanner has been done via perceptron neural network with three or four layers by back propagation algorithm for colored polyester fabrics. The results obtained for random training samples are not satisfactory but application of selective training samples for L*a*b* or RGB leads to good results, with better results obtained for the L*a*b* method. On the other hand, the color differences between calculation XYZ and real XYZ for unknown samples, are not only in agreement with the results of polynomials and regression methods, but are also better than the results obtained in previous studies where neural networkhad been used for colorimetric calibration of scanner.
H. Izadan, , S. A. Hosseini, , & and M. Ashori, (2022). Colorimetric Scanner Calibration for Textiles by Neural-Network. Journal of Advanced Materials in Engineering (Esteghlal), 22(2), 215-224.
MLA
H. Izadan; S. A. Hosseini; and M. Ashori. "Colorimetric Scanner Calibration for Textiles by Neural-Network", Journal of Advanced Materials in Engineering (Esteghlal), 22, 2, 2022, 215-224.
HARVARD
H. Izadan, , S. A. Hosseini, , and M. Ashori, (2022). 'Colorimetric Scanner Calibration for Textiles by Neural-Network', Journal of Advanced Materials in Engineering (Esteghlal), 22(2), pp. 215-224.
VANCOUVER
H. Izadan, , S. A. Hosseini, , and M. Ashori, Colorimetric Scanner Calibration for Textiles by Neural-Network. Journal of Advanced Materials in Engineering (Esteghlal), 2022; 22(2): 215-224.
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