• Journal of Biosystems Engineering
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• v.26 no.3
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• pp.279-286
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• 2001

The purpose of this study were to organize a sorting system, to develop an algorithm of image processing for the shape sorting, and to finally develop a scientific and objective shape sorting system of Korean Red-Ginseng for mechanization of the shape sorting. The results of this study are followed. 1. The shape sorting system of Korean Red-Ginseng consists of a control computer, a color CCD camera(WV-CP4110) for image processing, an image processing board(DT3153), and an image acquisition unit. 2. Many image processing skill, such as sliding, stretching, threshold, binary and D$\sub$t/ were used to analyze the shape sorting factors of Korean Red-ginseng. 3. The sorting accuracy of the shape sorting system for the Korean Red-Ginseng was 74.7%. It is 21.1% lower than that of human inspector. Although the system has low accuracy, using more cameras may improve its sorting accuracy.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.05a
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• pp.153-154
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• 2006

Development of sorting machine for photo diode and its control system is addressed. The sorting machine for optical communication device requires high positional precision because the alignment is one of the most important point in the sorting process. This sorting method describes how to detect the target chip's angle and position from the wafer. The machine vision system is used for the feedback control. This sorting machine is implemented by motion controller, machine vision and various solenoid valve and is interfaced with RS-232c, GPIB and PCI communication. This system gets the position accuracy within $1{\mu}m$ with our experiments.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2006.06a
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• pp.303-310
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• 2006

The sorting algorithms have been developed to take advantage of distributed computers. But the speedup of parallel sorting algorithms decrease rapidly with increased number of processors due to parallel processing overhead such as context switching time and inter-processor communication cost. In this paper, we propose a parallel sorting method which provides linear speedup of an optimal serial algorithm for a system with a large number of processors. This algorithm may even provide superlinear speedup for a practical system. The algorithm takes advantage of an interconnection network properties and its protocol.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.439-443
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• 2004

In this research, we describe the sorting conditions modeling by friction force. As in any mechanism which is required to provide good dynamic performance and high accuracy, performance evaluation of optimal control. To understand friction it is necessary to investigate the topography of the sliding surfaces in contact. Any surfaces, even apparently smooth surfaces, are microscopically rough. When two surfaces come into contact, the true contact takes place only at point where asperities come together. The sorting conditions of sorting mechanism with friction force is sorting force must be equal with force can sorting one highest veneer among loaded veneer. This is just a thing being sorted veneer have friction with under veneer and this friction disturb sorting at the same time. Hence, the sorting conditions evaluation is important to sorting one veneer must get under control friction with veneer.

• Journal of Biosystems Engineering
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• v.24 no.4
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• pp.325-334
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• 1999

The aim of this study was to present a groundwork for development of a sorting system of peeled garlics using machine vision. Images of various garlic samples such as sound, partially defective, discolored, rotten and un-peeled were obtained with a B/W machine vision system. Sorting factors which were based on normalized histogram and statistical analysis(STEPDISC Method) had good separability for various garlic samples. Bayes discriminant function and neural network sorting algorithms were developed with the sample images and were experimented on various garlic samples. It was showed that garlic samples could be classified by sorting algorithm with average sorting accuracies of 88.4% by Bayes discriminant function and 93.2% by neural network.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.19 no.5
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• pp.698-704
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• 2010

The machine vision system has been widely applied at automatic inspection field of the industries. Especially, the machine vision system shows good performance at difficult inspection field by contact method. In this paper, the automatic system of a slant method to inspect screw/bolt shape using machine vision is developed. The inspection system uses pattern matching method that search similar degree of the lucidity, the average lucidity, length and angle of inspection set up area using a circular scan and a line scan method. Also the feeding method for inspection product is the slant method, and feed rate is controlled by the ramp angle adjustment. This inspection system is composed of a feeding device, a transfer device, vision systems, a lighting device and computer, and is composed the sorting discharge system of the inferior product. The performance test carried out the feeding speed, the shape correct degree and the sorting discharge speed according to the type of screw/bolt. This sorting inspection system showed a satisfied test results in whole inspection items. Presently, this sorting inspection system is being used in the manufacturing process of screw/bolt usefully.

• ETRI Journal
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• v.37 no.2
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• pp.328-337
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• 2015

This paper applies acceleration/deceleration control-based velocity profiles to an infeed control algorithm for a cross-belt-type sorting system to improve the accuracy and performance of the system's infeed. The velocity profiles are of a trapezoidal shape and often have to be modified to ensure that parcels correctly synchronize with their intended carriers. Under the proposed method, an infeed line can handle up to 5,600 items/h, which indicates a 40% increase in performance in comparison with its existing handling rate of 4,000 items/h. This improvement in performance may lead to a reduction in the number of infeed lines required in a sorting system. The proposed infeed control algorithm is applied to a cross-belt-type sorting system (model name: SCS 1500) manufactured by Vanderlande Industries.

• Proceedings of the KIEE Conference
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• 2003.11b
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• pp.231-234
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• 2003

This paper describes the structure, operation, image processing, and decision making techniques of a color machine vision system designed for the automatic sorting of soybeans. The system consists of feeder, conveyor belt, line-scan camera, lights. ejector, and a PC Unlike manufactured goods, agricultural products including soybeans have quite uneven features. The criteria for sorting good and bad beans also vary depending on inspectors. We tackle these problem by letting the system learn the inspecting parameters from good samples selected manually by a machine user before running the system for sorting. Real-time processing has another importance In the design. Four parallel DSPs are employed to increase the processing speed. When the designed system was tested with real soybeans and the result was successful.

• Design & Manufacturing
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• v.16 no.4
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• pp.60-66
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• 2022

Recently, with the development of industry and the improvement of living standards, various wastes are generated along with the production of various products. Most of these wastes are used as containers for products, and plastic or aluminum is used. Various attempts are being made to automate the classification of these wastes due to the high labor cost, but most of them are solved by manpower due to the geometrical shape change due to the nature of the waste. In this study, in order to automate the waste sorting task, Deep Learning technology is applied to a robot system for waste sorting and a vision system for waste sorting to effectively perform sorting tasks according to the shape of waste. As a result of the experiment, a Deep Learning parameter suitable for waste sorting was selected. In addition, through various experiments, it was confirmed that 99% of wastes could be selected in individual & group image learning. It is expected that this will enable automation of the waste sorting operation.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.10
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• pp.2606-2615
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• 1994

Sorting time is one of the most important issues for auto IC test handling systems. In actual system, because of too much path, reducing the computing time for finding a sorting path is the key way to enhancing the system performance. The exhaustive path search technique can not be used for real systems. This paper proposes heuristic sorting algorithm to find the minimal sorting time. The suggested algorithm is basically based on the best-first search technique and multi-level search technique. The results are close to the optimal solutions and computing time is greately reduced also. Therefore the proposed algorthm can be effectively used for real-time sorting process in auto IC test handling systems.