• 농업과학연구
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• 제50권3호
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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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• 제16권3호
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• pp.272-280
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• 1991

The aims of this study were to investigate the feasivility of analyzing a few sorting factors such as size, coloration and defect of apples with a monochrome image processing system and to find apparent properties which could be effectively used for apple sorting. The results are summarized as follows. 1. A computer program was made to analyze the projection area, coloration and defect of an apple with a monochrome image processing system. 2. The algorithm developed to compute the projedtion area of an apple was between on the proportional relation between a given reference area and the corresponding number of pixels, and the computing time was 0.74 to 0.82 second depending on the size of apple. 3. The coloration of an apple was expressed as the ratio of the gray value of a reference color to that of a given bounded area of the stem end surface (defined as coloration index), and the computing time was about 3.0 seconds with this algorithm. 4. Defect of an apple could be isolated by lowpass filtering and image subtraction but it took about 20 seconds in computing time. 5. The coloration of the Fuji apple could be classified into 3 to 4 groups by the coloration index and also, it was found that the correlation coefficient between the indices and sugar contents was 0.74. 6. The coloration index obtained from a given bounded area of the stem end side of the Fuji apple could represent the coloration of total surface with a correlation coefficient of 0.922.

• 농촌계획
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• 제5권2호
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• pp.1-13
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• 1999

Packing house is the regional center in which packing, sorting, storage, and selling of harvested fruits are taken care of all together. It is located at the producing centers, and commercializes their apples. Apple grading policies of chief producing centers should concentrate on enhancing functions and roles of its local packing house. Consequently new packing house policies for enacting individual grading standards at national and local levels should be developed. This study is to develop Korea packing house on the basis of field survey in New York State. Increasing the utilization of packing house is the main key to the success of apple grading project. Therefore, effective arrangement and utilization of sorting facilities should be evaluated and new system which enables apple farms, local cooperatives, and corporations to joint-utilize packing house must to be established.

• Agricultural and Biosystems Engineering
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• 제1권2호
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• pp.106-110
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• 2000

An integrated on-line inspection system was constructed with seven cameras, half mirrors to split images. 720 nm and 970 nm band pass filters, illumination chamber having several tungsten-halogen lamps, one main computer, one color frame grabber, two 4-channel multiplexors, and flat plate conveyer, etc. A total of seven images, that is, one color image form the top of an apple and two B/W images from each side (top, right and left) could be captured and displayed on a computer monitor through the multiplexor. One of the two B/W images captured from each side is 720nm filtered image and the other is 970 nm. With this system an on-line grading software was developed to evaluate appearance quality. On-line test results with Fuji apples that were manually fed on the conveyer showed that grading accuracies of the color, defect and shape were 95.3%, 86% and 88.6%, respectively. Grading time was 0.35 second per apple on an average. Therefore, this on-line grading system could be used for inspection of the final products produced from an apple sorting system.

• 한국농업기계학회:학술대회논문집
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• 한국농업기계학회 2000년도 THE THIRD INTERNATIONAL CONFERENCE ON AGRICULTURAL MACHINERY ENGINEERING. V.III
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• pp.551-559
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• 2000

An integrated on-line inspection system was constructed with seven cameras, half mirrors to split images, 720 nm and 970 nm band pass filters, illumination chamber having several tungsten-halogen lamps, one main computer, one color frame grabber, two 4-channel multiplexors, and flat plate conveyer, etc., so that a total of seven images, that is, one color image from the top side of an apple and two B/W images from each side (top, right and left) could be captured and displayed on a computer monitor through the multiplexor. One of the two B/W images captured from each side is 720nm filter image and the other is 970nm. With this system an on-line grading software was developed to evaluate appearance quality. On-line test results to the Fuji apples that were manually fed on the conveyer showed that grading accuracies of the color, defective and shape were 95.3%, 86% and 91%, respectively. Grading time was 0.35 sec per apple on an average. Therefore, this on-line grading system could be used for inspection of the final products produced from an apple sorting system.

• 융합신호처리학회논문지
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• 제21권4호
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• pp.154-161
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• 2020

본 논문에서는 인간의 노력을 줄이고 정확성을 높이기 위해 사과의 색을 기반으로 하는 분류 시스템을 제안하였다. 제안된 분류 시스템은 카메라, 모터 및 라즈베리 파이로 구성되어 있고, 미성숙, 성숙, 익은 등으로 총 4가지 종류의 사과를 분류할 수 있다. 시장에서 다양한 종류의 사과를 100개 구입하여 무작위로 선택하여 평가하였다. 정확도는 95%였고 처리 시간은 사과당 약 8초였다. 제안한 시스템은 인력 감축에 유용할 것으로 예상된다.

• Journal of Biosystems Engineering
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• 제17권4호
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• pp.354-362
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• 1992

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, and to develop an algorithm for a high speed sorting. The results are summarized as follows : 1. The black/white image processing system used in this study showed a maximum error of 1.3% in area measurement with a reference figure while the focusing point of camera and location of the reference figure were changed within a certain range. 2. As the result of evaluating four automatic image segmentation algorithms with apple images, Histogram Clustering Method was the best in terms of computation time and accuracy. 3. The fast algorithm for analyzing size and coloration of apple was developed. 4. The whole surface of an apple could be captured in an image frame with two mirrors installed on the both sides of the sample. The total area of the image representing the whole surface showed a correlation of 0.995 with the weight of apple. 5. The gray level when a particular band pass filter was mounted on the camera showed high correlation with 'L' and 'a' values of Hunt color scale and could represent the coloration of apple.

• 한국농업기계학회:학술대회논문집
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• 한국농업기계학회 1993년도 Proceedings of International Conference for Agricultural Machinery and Process Engineering
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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 Biosystems Engineering
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• 제17권4호
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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.

• 한국농업기계학회:학술대회논문집
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• 한국농업기계학회 2000년도 THE THIRD INTERNATIONAL CONFERENCE ON AGRICULTURAL MACHINERY ENGINEERING. V.III
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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.