## 1 Introduction
There are several traditional methods available for the detection of Sudan dyes in red chili like Thin-Layer Liquid Chromatography (TLC) [7], High-Performance Liquid Chromatography [14], and their modified usage like HPLC with photodiode arrays [15]. However, these methods are laborious and require skilled workers. Moreover, they are not portable, and sending samples to distant laboratories took considerable time and effort. Imaging techniques have been widely used in agriculture and food industries for quality control; inspection; and monitoring of growth, disease, etc. However, a digital camera, similar to the human eye, is only capable of working in a visible spectrum of electromagnetic radiations. This limits the examination to physical attributes like the color, size, and shape of the object. To determine the chemical properties of an agro-food, spectroscopic methods are usually utilized which provide the  
Figure 1: Visual difference of pure and oil-adulterated red chili. mean spectrum of a sample without any spatial information [16]. Thus, these methods are limited to homogenized samples and cannot be used for the inspection of heterogeneous objects. In recent years, several vibrational spectroscopic techniques like Raman, Infrared (IR), and Ultraviolet-Visible (UV-Vis) have been utilized with chemometric analysis to detect and measure various properties of red chili. [PERSON] et al. presented a system that can measure the moisture and capsaicinoids content of red chili by using Visible and Near-Infrared (VIS-NIR) spectroscopy [17]. [PERSON] and [PERSON] proposed the use of Fourier transform near-infrared (FT-NIR) spectroscopy for the detection of aflatoxin \(B1\) in red chili [18]. [PERSON] et al. present an approach for the detection of adulterants in grounded Sichuan pepper powder using VIS-NIR spectroscopy [19]. [PERSON] et al. studied the feasibility of utilizing Near-Infrared (NIR) and Raman Spectroscopy for the detection of Sudan dye in red chili powder [20]. They spiked red chili powder with Sudan I dye and used Partial Least Squares Discriminate Analysis (PLS-DA) for the detection of Sudan dye. Similarly, [PERSON] et al. utilized UV-VIS, Raman, and FT-NIR spectroscopy techniques for the detection of Sudan dye in various spices including paprika. They mixed Sudan dye in chloroform and spiked spices with the solution. They further used K-Nearest Neighbor (KNN), Soft Independent Modeling of Class Analogy (SIMCA), and PLS-DA for classification. [21; 22]. Hyperspectral imaging combines the power of both tools (digital camera and spectroscopy) and extends the capabilities to a new dimension [23]. As a traditional probe-based spectroscopy method, it acquires the spectrum of a sample, and conventional imaging techniques map this information in spatial dimension for visualization. Hyperspectral cameras were developed and utilized initially for remote sensing [24], but the recent advancement in technologies has introduced this tool in laboratories. Thus, researchers started utilizing its powers in various fields like agriculture [25], food [26], pharmaceutical [27], forensic [28], and environment [29]. This tool has several advantages such as being precise, expeditious, noninvasive, and multi-analytical, which enable it to predict several attributes (physical and chemical) with a single acquisition. The Hyperspectral Imaging (HSI) system provides the data in the form of a \(3D\) cube usually known as hypercube [30]. The hypercube consists of multiple spatial images stacked concerning wavelength spectrum. The coordinates of a hypercube are labeled as \(x\), \(y\), and \(\lambda\), where \(x\) and \(y\) represent the spatial coordinates, and \(\lambda\) is the spectral coordinate [31]. In our previous work [32], we have utilized the (VIS-NIR) HSI system with a one-class Support Vector Machine (SVM), to detect powder adulterants in grounded red chili. To ensure purely grounded red-chili, we purchased whole chili samples from the market and ground it by ourselves. Our system was up to 99% effective.