• The Korean Journal of Applied Statistics
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• v.16 no.1
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• pp.129-140
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• 2003

This study was to develop a fruit sorting system using statistical image processing. Histogram was used to compare fruit colors to standard fruit color and edge detector using Wilcoxon test was used to calculate an accurate geometrical characteristics of fruit including perimeter, area, major axis and minor axis length and roundness. The experimental result obtained from using our system for sorting apples was presented.

• Korean Journal of Agricultural Science
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• v.50 no.3
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• pp.415-424
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• 2023

The task of sorting and excluding blemished apples and others that lack commercial appeal is currently performed manually by human eye sorting, which not only causes musculoskeletal disorders in workers but also requires a significant amount of time and labor. In this study, an automated apple-sorting machine was developed to prevent musculoskeletal disorders in apple production workers and to streamline the process of sorting blemished and non-marketable apples from the better quality fruit. The apple-sorting machine is composed of an arm-rest, a main body, and a height-adjustable part, and uses object detection through a machine learning technology called 'You Only Look Once (YOLO)' to sort the apples. The machine was initially trained using apple image data, RoboFlow, and Google Colab, and the resulting images were analyzed using Jetson Nano. An algorithm was developed to link the Jetson Nano outputs and the conveyor belt to classify the analyzed apple images. This apple-sorting machine can immediately sort and exclude apples with surface defects, thereby reducing the time needed to sort the fruit and, accordingly, achieving cuts in labor costs. Furthermore, the apple-sorting machine can produce uniform quality sorting with a high level of accuracy compared with the subjective judgment of manual sorting by eye. This is expected to improve the productivity of apple growing operations and increase profitability.

• Journal of Biosystems Engineering
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• v.17 no.4
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• pp.363-369
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• 1992

The aim of this study was to examine the blurring effects on performance of the experimental fruit grader in grading Fuji apples by size and coloration of the whole surface of individual apples. The grader consisted of a black/white image prcessing system, one camera, and utilized the algorithm developed for high speed sorting in the previous study. The results are summarized as follows : 1. With the algorithm developed in the previous study, it took 0.27~0.33 second in analyzing the size and coloration of an apple, and relative errors were within 3% for size and 1.3% for coloration. 2. The effect of blurring increased linearly with the conveying speed of apple and showed more significant effect on detection of coloration than on determining of size. 3. Considering the blurring effect, capacity of the experimental fruit grader was estimated to 7,500 apples per hour.

• Journal of Biosystems Engineering
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• v.24 no.3
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• pp.267-274
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• 1999

An internet and network based software and related interface have been developed, which can remotely control and manage an on-site operating system. Developed software modules were composed of two parts: monitoring/management modules and control/diagnosis modules were developed for the network status, warehouse, production and selling status. Modules of control with diagnosis were developed for the on-site operating system and interface. Each module was integrated and the whole modules have been tested with an automatic mushroom grading/sorting system which was built in a laboratory. Developed software modules worked successfully without any uncommon situations such as system down caused by the software or data transfer error. Each software module was developed independently in order to apply easily to other existing on-site systems such as rice processing centers, fruit and vegetable sorting, packaging and distribution centers scattered over the country.

• Journal of Biosystems Engineering
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• v.15 no.1
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• pp.23-32
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• 1990

Geometrical characteristics of fruit including perimeter, projected area and length of minor and major axis were calculated by computer programs to be used in fruit sorting by image processing system. The results are summerized as follows. 1. A program calculating perimeter, projected area, and length of minor and major axis by edge detection and chain code was developed. 2. Geometrical characteristics of given figures were calculated to verify the program and the discrepancies from the measured values were about 5%. 3. Regression models for estimating volums of apples were developed and regression coefficients for each variety were found. 4. Abnormal apples could be recognized by comparing the ratio of minor axis to major axis and the standard value was proposed.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1993.10a
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• pp.1292-1301
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• 1993

This study was intended to examine feasibility of sizing and color grading of Fuji apple with black/white image processing system , to develop a device with which the whole surface of an apple could be captured by one camera , to develop an algorithm for a high speed sorting , and to examine the effects of blurring on the performance of the experimental fruit grader.

• Journal of Sensor Science and Technology
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• v.11 no.2
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• pp.93-101
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• 2002

The quality of agricultural products is classified with various factors which are measured and determined by destructive and/or nondestructive method. NIR spectrum analysis method is used to determine internal qualities such as a brix and an acidity. CCD color camera is used to measure external quality like color and a size of fruit. Today, nondestructive methods are widely researched. The quality and the grade of fruit loaded into a cup automatically and measured in real time by camera and NIR system is determined by infernal and external factors. This paper proposes modified boundary tracking algorithm which detects the contour of fruit's color image and make chain code faster than conventional method. The chain code helps compute a size of fruit image and find multiple loading of a fruit in single cup or fruit between two cups. The designed classification system sorts a citrus at speed of 8 fruit/s, with evaluating a brix, an acidity and a size grade.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.2
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• pp.421-441
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• 2021

Fruit detection in orchards is one of the most crucial tasks for designing the visual system of an automated harvesting robot. It is the first and foremost tool employed for tasks such as sorting, grading, harvesting, disease control, and yield estimation, etc. Efficient visual systems are crucial for designing an automated robot. However, conventional fruit detection methods always a trade-off with accuracy, real-time response, and extensibility. Therefore, an improved method is proposed based on coarse-to-fine multitask cascaded convolutional networks (MTCNN) with three aspects to enable the practical application. First, the architecture of Fruit-MTCNN was improved to increase its power to discriminate between objects and their backgrounds. Then, with a few manual labels and operations, synthetic images and labels were generated to increase the diversity and the number of image samples. Further, through the online hard example mining (OHEM) strategy during training, the detector retrained hard examples. Finally, the improved detector was tested for its performance that proved superior in predicted accuracy and retaining good performances on portability with the low time cost. Based on performance, it was concluded that the detector could be applied practically in the actual orchard environment.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2000.11c
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• pp.513-520
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• 2000

An integrated grader which measures soluble solid content, color and weight of fresh apples was developed by NAMRI. The prototype grader consists of the near infrared spectroscopy and machine vision system. Image processing system and an algorithm to evaluate color were developed to speed up the color evaluation of apples. To avoid the light glare and specular reflection, an half-spherical illumination chamber was designed and fabricated to detect the color images of spherical-shaped apples more precisely. A color revision model based on neural network was developed. Near-infrared(NIR) spectroscopy system using NIR reflectance method developed by Lee et al(1998) of NAMRI was used to evaluate soluble solid content. In order to observe the performance of the grader, tests were conducted on conditions that there are 3 classes in weight sorting, 4 classes in combination of color and soluble solid content, and thus 12 classes in combined sorting. The average accuracy in weight, color and soluble solid content is more than about 90 % with the capacity of 3 fruits per second.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1993.10a
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• pp.1302-1311
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• 1993

In the 90 years or so since the beginning of the 20 th century , orchard growing and agricultural fields in Japan have undergone considerable change in terms of production volume, a seen in Fig. 1. as this change in volume progressed, sorting and packing machines have also grown from the first wooden tools, almost too simple to be called " machines" into sophisticated devices that bring together diverse technologies such as machinery , electronics, and optics. Nowadays, Japan/s agricultural industry is facing unprecedentedly serious labor shortage and the rapid aging of its experienced growers and producers, In additions, Japan has changed from a society oriented towards high-volume production and consumption to a more selective society which prefers smaller volume with the tastes of naturally ripended produce. With consumer trends changing there is a new demand on the part of growers for equipment that can not only measure the external quality of produce , but can measure inte nal quality as well.