A low-cost multi-perspective projection imaging system was developed based on a plane mirror, to study table grape clusters and determine the quality of the cluster shape and color. In this system, the field of view of the monocular camera was expanded using two front-surface plane mirrors and optical information of the whole surface of the grape cluster was collected. Through image processing methods, the virtual/real image regions of the cluster were segmented, the virtual regions were enlarged based on the same height of the hanging grape clusters, and three clusters at the same height were obtained at 120° intervals. The parameters of cluster regions and contour widths were extracted to assess the external shape of grape clusters, and 95.5% accuracy was achieved for grading of the grape clusters compared to manual grading. The hue, saturation, and intensity (HSI) color space was transformed from the red, green, blue (RGB)-colored image, the typical color region of maturity was obtained from Hue channel image, and the ratio of colored surface area of grape was calculated. The color of the grape cluster was classified according to the ratio of colored cluster area, with an accuracy rate of 81%. The results indicate that this multi-perspective approach to simultaneously capture images can be applied to grade the external quality of grapes and can be applied to on-line shape and color measurement.