Development of a lemon sorting system based on color and size

Abstract

Grading systems give us many kinds of information such as size, color, shape, defect, and internal quality. Among these color and size are the most important features for accurate classification and/or sorting of citrus such as oranges, lemons and tangerines. Basically, two inspection stages of the system can be identified: external fruit inspection and internal fruit inspection. The former task is accomplished through processing of color images, while internal inspection requires special sensors for moisture, sugar and acid contents. In this paper, an efficient algorithm for grading lemon fruits is developed and implemented in visual basic environment. The system consists of two CCD cameras, two capture cards, an appropriate lighting system, a personal computer and other mechanical parts. The algorithm initially extracts the fruit from the background. The samples of different grades of lemon are situated in front of the cameras and are calibratted off-line. Then information on the HSI color values and estimated volumes of fruits are extracted and saved in a database. By comparing the information during sorting phase with the available information inside the database, the final grade of the passing fruits are determined. This algorithm can be easily adapted for grading and/or inspection of other agricultural products such as cucumber and eggplant.   Key words: Lemon, sorting, volume, image processing, machine vision, HSI color.