The sorting operations of cherry are conducted manually by cherry farmers; however, they require skillful workers to examine each fruit, and evaluation is subject to variation. This study analyzed the performance of an automatic cherry sorting system. The key to sorting cherries is to sort the fruits accurately without producing damage, along with quick size estimation and grade identification. An image analysis system using the hue saturation lightness (HSL) color model to identify the grade of cherries was implemented. Size was estimated by the equator diameter of the fruit, and grade was determined by the percentage of colored area on the surface of the fruit. A prototype system for automatic cherry sorting into three grades was developed. A second version of the prototype was developed to include size estimation. In both prototypes, an air eject mechanism with individual collection bins were prepared for a non-invasive handling of the fruits. A stable accuracy of 72.4% for size estimation and 82.5% for grade identification were achieved. The findings favor the use of automatic systems for the sorting of cherries according to fruit grade in combination with fruit size.