## 4 Summary and Conclusions  
The influence of carpet structure and resultant texture on color perception has been investigated in this study. Different shades of two colors were considered under three different illuminants to analyze the subsequent variability caused by carpet features. Color values have been evaluated by the CIELAB scale, where it has been observed that the L*, a*, and b* values were reduced with the increasing concentration of dye/colorant molecules based on the incident light's absorption, scattering, and reflection. Carpet features have been found to be affecting the L*, a*, and b* values either significantly or insignificantly, depending on the dye and shade conditions. In the case of gradual shading from light to dark light, significant variations in L*, a*, and b* values can be observed based on the presence of colorant molecules on the light-reflecting loop-arch planes. For a darker shade, more colorants being present in the loop-arch plane can minimize the difference in perceived lightness (L*) for different carpets dyed with the same condition. However, more colorants can also cause significant variations among different carpets on the chroma scale (a* and b* values) in the same dyed condition. However, such variations can again become insignificant if the corresponding values are very small, which indicates a shift to the grey scale (CIE L axis). Different illumination sees similar trends in L*, a*, and b* values for different carpets, however, in varying degrees due to the different power distribution of the colored wavelengths of incident light. MLR analyses were performed to assess how the significant parameters affected the L*, a, and b* values. Regression equations were developed from the MLR analyses, which can estimate the L*, a*, and b* values under a definite illuminant with a definite color. From the MLR, it is noticeable that based on the absorption and reflection pattern of the corresponding dye/colorant molecules, pile height and stitch rate could significantly affect color perception. The effect of the dye/colorant concentration is significant in all of the causes due to the gradual shading process, significantly contributing to every prediction of the carpet in terms of chroma and lightness values. This study implies that carpet structures can affect color perception either significantly or insignificantly based on color, shade, and illuminant types. While consumers buy carpets based on the primary perception of the color, it can be significantly affected by the interaction of carpet features and different illuminants of the interior settings, which could greatly affect customer satisfaction. Hence, to prevent the mismatch of the color appearance of carpets under different illuminants, it is necessary to accurately predict the color. This study is initiated with two different colors to investigate the effect of carpet structures and shades over color perception under different illuminants as a part of long-term project. Other colors and carpet properties could be included in future studies. This could provide holistic information of color variations in the predicting models. The equations of the regression model could be further utilized to develop an app which will be efficient in addressing the variety of color perceptions for different carpet structures, colors, shades, and illuminants. When the carpets will be scanned through the app, it will generate different images of the carpets for different illuminants that can facilitate the carpet selection of consumers. S.M. : conceptualization, designing experiments, writing, data analysis, supervision, funding acquisition, project administration. LZ.C. : Literature review, conducting experiments, writing, and data analysis. P.R.H. : conceptualization, supervision, funding acquisition, project administration. A.P. : conceptualization, supervision, funding acquisition, project administration. S.I.T. : Literature review, conducting experiments, writing, and data analysis. M.M.I. : Literature review, writing, and data analysis.