# Hyperspectral Imaging System with Rotation Platform for Investigation of Jujube Skin Defects
## 1 Introduction
Whole surface inspection is a challenging problem until now that affects the comprehensive and reliability of the grading results of fruits, since information leakage and repetition of fruit surface images or spectral data during color and defect detection could affect successive classification. Although many efforts have been made by worldwide grading engineers for decades, a thorough and practical solution is still not available so far [1]. Capturing images from different views with multiple cameras or with the assistance of mirrors is a common method used in the inspection of fruits to obtain much or whole surface of fruits [1; 8; 9; 22]. [PERSON] et al. [1] developed an imaging system with two mirrors on opposite sides of the apple to capture four sides of an apple sitting in a shallow cup by using two cameras mounted above and below the conveyor. This method allows most of the apple surface to be taken, but portions of the apple surface are blocked by the supporting cup. [PERSON] et al. [22] built a vision system with mirrors to measure the three dimensional (3D) shape of the strawberries. Nine mirrors around the object at an angle were used to reflect side views of the object, and the side views were taken simultaneously with a digital camera. The 3D shape was reconstructed from the nine-sided views by the volume intersection method. [PERSON] et al. [9] used computer vision system with mirrors for whole surface imaging of apple suspended by two thin wires. Results revealed that taking one single image using the four or six mirror configurations could catch the image of almost 100% of the surface of apples. However, for testing, an individual apple had to be suspended by two thin wires, which restricts its application in commercial in-line sorting lines. [PERSON] et al. [8] developed a computer controlled system with color cameras for in-line detection of apple defects. In this system, the apples placed on rollers were rotating while moving and three color cameras were placed on the line. Each camera captured three images from each apple. A total of nine images obtained for each apple allowed the entire surface to be scanned. The defects, including the stem-ends and calyxes, called regions of interest (ROIs), were segmented and counted in each of the nine images. Since a calyx and stem-end cannot appear at the same image, an apple is defective if any one of the nine images has two or more ROIs. Good separation between normal and defective apples was obtained; however, different defect types could not be distinguished. The above-mentioned studies about how to achieve whole surface inspection of fruits are suitable for computer vision with snapshot camera(s), while the techniques for whole surface scan or increasing scannable surface area in one scan pass about fruit are not examined thoroughly for line-scan machine vision system such as push-broom hyperspectral imaging (HSI) system. [PERSON] et al. [23] built a hyperspectral imaging system with rotation unit employed two motor driven rollers to obtain all-round hyperspectral image of the whole peach for the study of decayed on peach surface. [PERSON] et al. [22] developed an optical system for push-broom hyperspectral camera to obtain the whole surface spectral data of a round object. The system uses four mirrors to view a rotating round object from two opposite sides and project a combined two-view image onto the aperture of a push-bloom HSI camera. The image of the whole surface of the round object can be used to detect defects located on any part of that surface. In order to obtain the two side views that include the areas around the poles, the distance from the inside mirrors to the outside mirrors and the inclination angles of the outside mirrors need thoughtful design. In their study, calibration tests showed that the system could detect six simulated defects dispersed evenly over the surface of an apple, without missing or repeating a defect, for 78% of the apple fruits tested.