• 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.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1999.12a
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• pp.615-625
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• 1999

• Resources Recycling
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• v.17 no.6
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• pp.43-49
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• 2008

In this study, a scrap sorting system using a color recognition method has been developed to automatically sort out specified materials from a mixture, and its application as been examined in the separation of Cu and other non-ferrous metal parts from a mixture of iron scraps. The system is composed of three parts; measuring, conveying and ejecting parts. The color of scrap surface is recognized by the measuring part consisting of a line-scan camera, light sources and a frame grabber. The recognition is program-controlled by a image processing algorithms, and thus only the scrap part of designated color is separated by the use of air nozzles. In addition, the light system is designed to meet a high speed of sorting process with a frequency-variable inverter and the air nozzled ejectors are to be operated by an I/O interface communication with a hardware controller. In the functional tests of the system, its efficiency in the recognition of Cu scraps from its mixture with Fe ones reaches to more than 90%, and that in the separation more than 80% at a conveying speed of 25 m/min. Therefore, it is expected that the system can be commercialized in the industry of shredder makers if a high efficiency ejecting system is realized.

• KOREAN JOURNAL OF PACKAGING SCIENCE & TECHNOLOGY
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• v.26 no.2
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• pp.61-69
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• 2020

As post-harvest processes of onions are carried by a 20 kg-net package which results in high-cost and low-efficiency, especially, the insufficient drying and physical damage of onions after harvesting leads to a huge second loss in storage, we had developed a low-cost, high-efficiency post-harvest bulk handling machinery system by collecting onions on a farm using ton-bags, drying with forced air circulation, and sorting/packaging. The post-harvest bulk handling machinery system consisted of 6 devices, and this study designed an automatic feed hopper with a feeding rate control device, an inclined belt conveyor with a two-step chute, and an automatic pallet unloading device for feeding onions into the sorting/packing line. This study also analyzed the performance and control of the total system. The device had 1-ton handling capacity, but the operational condition was set to increase the capacity. The three-step filling method of pallet by the velocity control of the inclined belt conveyor was applied in the post-harvest bulk handling machinery system for the prevention of physical damage. If one worker was set to operate the total system, the time required to complete one palletized load was approximately 5 minutes and 5 seconds. The calculated daily handling capacity was approximately 94 tons, when the daily actual working time was 8 hours. When the developed system was applied to the managerial size of 2,000 ton, the processing cost per ton of the system was decreased by 19.5%, compared with the existing 20 kg-net package-based handling. The developed post-harvest bulk handling machinery system would be a good substitute for the rapid decline and aging of rural labor.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.1027-1030
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• 1999

Recently many efforts on the development of automatic processing system for delivery sequence sorting have been performed in ETRI, which requires the use of postal 4 state bar code system to encode delivery points. This paper addresses the issue on the reduction of reading error in postal 4 state raster beam based bar code reader by adjusting measured values of bar code width to its average value over each interval. The test results show that the above method reduces the average reading error rate approximately by 90-100%.

• Journal of Biosystems Engineering
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• v.29 no.2
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• pp.167-174
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• 2004

Density is a physical property which contains information relating to the internal quality of fruits and vegetables, and can be used as an index for nondestructive quality evaluation. Density sorting has been employed by farmers for some agricultural products since ancient times. In this study, an automatic density measuring system based on the platform scale or water displacement method was developed for density sorting of watermelon. It consisted of water tan, load cell, net tray, electric motor, limit switch, control system and its program. The resolution of density was 0.001 g/㎤. In order to calibrate and evaluate the accuracy, the density was measured using a balloon kept in cold water. It showed 1.002 g/㎤ which almost correspond to real density of water. Test results with 6 watermelons and 3 replications showed that the standard deviations of the dens were 0.001∼0.004 g/㎤. The relationship between density and internal quality of watermelon was investigated using the system. The densities of hollow watermelons were less than 0.950 g/㎤, it was apparent that the density of the watermelon was related to the degree of hollowness. But the soluble solid contents and internal defects could not be estimated from the density.

• Korean Journal of Poultry Science
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• v.22 no.4
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• pp.233-238
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• 1995

A computer vision system was built to generate images of a single, stationary egg. This system includes a CGD camera, a frame grabber, and incandescent back lighting system. Image processing algorithms were developed to inspect egg shell and to sort eggs. Those values of both gray level and area of dark spots in the egg image were used as criteria to detect holes in egg and those values of both area and roundness of dark spots in the egg image were used to detect cracks in egg. For a sample of 300 eggs, this system was able to correctly analyze an egg for the presence of a defect 97.5% of the time. The weights of eggs were found to be linear to both the projected area and the perimeter of eggs viewed from above. Those two values were used as criteria to sort eggs. The coefficients of determination(r$^2$) for the regression equations between weights and those two values were 0.967 and 0.972 in the two sets of experiment. Accuracies in grading were found to be 95.6% and 96.7% as compared with results from sizing by electronic weight scale.

• Journal of Biosystems Engineering
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• v.24 no.2
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• pp.153-158
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• 1999

As a basic research for the development of the automatic grading and sorting system for dried oak mushrooms, the device to acquire both cap and gill side images of mushroom has been developed and neural network based side recognition and quality grading has been proposed via inputting both side images. 20 quality grades have been selected considering the requirement of grade classifications imposed by the mushroom company. Developed DC motor driven‘V’type reversing device for the image acquisition of both side images of mushroom showed more than 95% success. Most error was caused by very small size mushrooms with a radius of around 1cm. However, it required a further research to reduce the reversing time. Grading and side recognition were performed via inputting normalized size factors and average gray levels of $8{\times}8$ grids converted from the raw images of both surfaces to the multi-layer back propagation(BP) network. Accuracy of the grading showed about 88.5% and the total grading time including reversing operation was around 2 seconds.

• The Transactions of the Korea Information Processing Society
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• v.7 no.1
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• pp.146-155
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• 2000

This paper describes a 4-state bar code called HANGUL 4 ST that has been specifically designed for automatic processing of the letter mails, A HANGUL 4 ST bar code is a necessary data base that is applied data capture and data carrier with it all the information necessary for sorting, the amount capture for transportation of mail items, and valued-added services such as indicia, tracking and trace. The 4-state bar code information contents are composed of a postal code, delivery point, customer information including customer identification number and name, and parity bits for error detect and correct. The data density capability of HANGUL 4 St allows all useful sorting data and customer data to be encoded on one label. This supports better automatic processing in mail items, higher level of customer service and more efficient operation.

• Journal of Bio-Environment Control
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• v.1 no.1
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• pp.37-51
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• 1992

Quantizing and extracting visual features of mushroom(Lentinus edodes L.) are crucial to the sorting and grading automation, the growth state measurement, and the dried performance indexing. A computer image processing system was utilized for the extraction and measurement of visual features of front and back sides of the mushroom. The image processing system is composed of the IBM PC compatible 386DK, ITEX PCVISION Plus frame grabber, B/W CCD camera, VGA color graphic monitor, and image output RGB monitor. In this paper, an automatic thresholding algorithm was developed to yield the segmented binary image representing skin states of the front and back sides. An eight directional Freeman's chain coding was modified to solve the edge disconnectivity by gradually expanding the mask size of 3$\times$3 to 9$\times$9. A real scaled geometric quantity of the object was directly extracted from the 8-directional chain element. The external shape of the mushroom was analyzed and converted to the quantitative feature patterns. Efficient algorithms for the extraction of the selected feature patterns and the recognition of the front and back side were developed. The developed algorithms were coded in a menu driven way using MS_C language Ver.6.0, PC VISION PLUS library fuctions, and VGA graphic functions.