Robust Apple Segmentation using Fuzzy Logic

A fuzzy logic-based image processing technique is presented in this paper to segment multi-colored apples on a tree robustly. The method is based on a fuzzy inference system and the fuzzy c-means algorithm. The proposed technique efficiently segments apples that contain multiple colors. This work not only segments apple but also provides an initial observation to monitor the growth of an apple based on its color. For some types of apples, the color is green at the initial stage, then turns yellow, and followed by red when apples are ready for packaging. The fuzzy logic based processing technique robustly distinguishes between green, yellow, and red apples. The proposed technique is evaluated qualitatively by visually comparing the detection of a number of apples in three datasets. It is shown through evaluation that fuzzy logic-based image processing technique can effectively segment the apples under different challenging conditions.