A Real-Time Apple Grading System Using Multicolor Space

Hayrettin Toylan,Hilmi Kuscu

doi:10.1155/2014/292681

Abstract

This study was focused on the multicolor space which provides a better specification of the color and size of the apple in an image. In the study, a real-time machine vision system classifying apples into four categories with respect to color and size was designed. In the analysis, different color spaces were used. As a result, 97% identification success for the red fields of the apple was obtained depending on the values of the parameter “a” of CIE L*a*b*color space. Similarly, 94% identification success for the yellow fields was obtained depending on the values of the parameter y of CIE XYZ color space. With the designed system, three kinds of apples (Golden, Starking, and Jonagold) were investigated by classifying them into four groups with respect to two parameters, color and size. Finally, 99% success rate was achieved in the analyses conducted for 595 apples.

Highlights

Turkey has the third place in the world after China and the USA with a 2.782.370-ton apple production [1]
Image acquisition device used for this research is a 1.3 mega pixel (H × V = 1280 × 1024 pixel) resolution 25 fps Complementary Metal Oxide Semiconductor (CMOS) camera with a manually adjustable 6 mm focus length which is mounted on camera, C-mount lens, a lighting system, 600 mm × 670 mm × 300 mm white painted diffusely illuminated tunnel with four fluorescent lamps, a conveyor belt on which fruits are placed, and automatic sorting unit
It is converted to the Commission Internationale de L.Eclairage (CIE) XYZD55 color space by taking into consideration the D55 illumination conditions in the systems using the von Kries transforms matrix

Summary

Introduction

Turkey has the third place in the world after China and the USA with a 2.782.370-ton apple production [1]. Color and size classification of the apples were done by employees by just looking at them. It is hard to classify apples that are in similar colors yet in different types. Most of the fruit classification systems built in Turkey classify fruits according to their size and mass. Machines based on mass of fruit need a mass measurement system. This type of machines can be efficiently used for 2000 kg/h. Different shape of circular materials or holey wooden staffs are used for eliminating the fruits according to their size. By using these machines a person can classify 100–200 fruits per hour. Even if centrifugal technology using machines are commonly used in our country [2], the leading actors of the sector think that it is not good enough for latest business conditions

Methods

Results

Conclusion