## 1 Introduction
In turn, no statistical model was developed to predict the color appearance of textile products accurately and conveniently. [PERSON] et al. [19] investigated the effects of fabric surface structure over color attributes such as lightness, chroma and hue. They identified significant effect of fabric surface over the lightness values. They addressed several color measuring scales and developed models to effectively reduce the impact of fabric texture over color measurements [19; 20]. Given that, a more varied and significant textural difference can be observed in carpets and other interior textiles. Hence, perceived color differences can be more discernable for carpets with same colored yarn. Moreover, the probability of color mismatches under different illuminants is significantly higher while such textiles are in question. To date, no published research has scientifically characterized and modeled the color appearance of interior furnishing textile products under different illuminants. Carpet is one of the most widely used interior furnishing textile products, and wool fiber-based carpets mainly cater to the luxury consumer markets. In fact, [PERSON] et al. [21] found that luxury consumers prefer to view their carpets under a particular illuminant. Therefore, one of the most important concerns of carpet manufacturers, interior designers, and visual merchandisers of retail stores is the color appearance of carpets because it significantly influences the purchasing decisions of consumers. Thus, there is a critical need to characterize, and develop color predictive model for the perceived appearance of carpets under different illuminants in consideration of key carpet features scientifically and computationally. Several researchers have tried to characterize the carpet appearance. Based on digital image analysis, [PERSON] [22] has created a method to address the carpet appearance via constructional parameters. In the study addressed carpet constructional parameters were pile height, pile type, gauge, stitch rate, carpet density. Here, carpet pile height refers to the length of the fiber tufts that are visible in the carpet. Gauge is the distance from one needle to the subsequent needle, whereas stitch rate is the number of stitches that occur within one inch. Pile density is the weight of the pile yarn per unit volume of carpet. The spectrophotometric and colorimetric properties of yarn and carpets have been compared by [PERSON] et al. [23]. They discovered that the carpet's reflectance is always inferior to those of the yarn, regardless of the concentration of the dye used. [PERSON] and [PERSON] [24] have developed a method to identify the carpet through the decomposition of the complex image of the carpet using the components of patterns, pixels of color, and contours. [PERSON] [25] looked into how mechanical wear on carpet pile affects the carpet's apparent color. However, these studies did not consider the variations in illumination as well as the varied formation of carpet structures [22; 23; 24; 25]. Therefore, the goal of this study is to develop statistical models that can be successfully utilized in color prediction of carpets under different illuminants. The overall objective in this research is to propose a Multiple Linear Regression (MLR) model for identifying the significant parameters affecting the apparent color of carpets. In order to fulfill the above-mentioned critical need, the MLR model will be developed by considering the features of the carpets.