• Journal of the Korean Society of Industry Convergence
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• v.24 no.5
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• pp.555-562
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• 2021

In this paper, we propose a sorting method for extracting accurate license plate information, which is currently used in Korea, after detecting objects using YOLO. We propose sorting methods for the five types of vehicle license plates managed by the Ministry of Land, Infrastructure and Transport by classifying the plates with the number of lines, Korean characters, and numbers. The results of experiments with 5 license plates show that the proposed algorithm identifies all license plate types and information by focusing on the object with high reliability score in the result label file presented by YOLO and deleting unnecessary object information. The proposed method will be applicable to all systems that recognize license plates.

• Proceedings of the KIEE Conference
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• 1988.11a
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• pp.64-67
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• 1988

This paper proposes a algorithm to obtain a time-varing system parameters for the optimal controller. The proposed algorithm is enlarged from tile optimal sorting algorithm. It applies to Bang-Bang control and compares with CGD Method. We confirm that the proposed algorithm is excellent.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.275-280
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• 1990

A neural network method is applied for recognizing the orientation o f individual parts being fed from a bowl feeder. The system is designed in such a way that a part can be discriminated and sorting according to every possible stable orientation without implementing any a mechanical tooling. The operation of the bowl feeder is based on a 2D image obtained from an array of fiber optic sensor located on the feeder track. The acquired binary image of a moving and vibrating part is used as input to a neural network which, in turn, determines t he orientation of the part. The main task of the neural network, here is to synthesize the appropriate internal discriminant functions for the part orientation using the part features. A series of the experiments reveals several promising points on performance. Since the operation of the feeder is highly programmable, it is well suited for feeding and sorting small parts prior to small batch assembly work.

• Bulletin of the Korean Chemical Society
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• v.6 no.4
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• pp.241-246
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• 1985

Twenty trace elements were determined in 250 Korean potsherds and 5 clay samples by instrumental NAA. In the absence of identified samples of known origin, the potsherds were classified by a hierarchical centroid sorting method to construct a dendrogram. From this dendrogram 61 well-defined samples were selected to form 8 subclasses and five elements such as Cr, Cs, Sm, Sc and Th were supposed to be the main contributors for the classification. The 61 samples along with 5 clay samples were reclassified by means of minimal spanning tree as well as the hierarchical centroid sorting method by using 5 elements selected. As the results, the potsherds of certain classes defined in this work could be taken as a basis for latter identification and served as batches of identified species.

• Journal of IKEEE
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• v.23 no.3
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• pp.978-983
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• 2019

Under the influence of Autonomous Driving and AI, it is important to accurately recognize and judge objects through cameras. In particular, since a method of recognizing an object using a camera can obtain a large amount of information visually compared to other methods, many image signal processing methods have been studied to extract an accurate image. In addition, a lot of research is being carried out to implementation about hardware. In this work, we compare the principles and characteristics of the sorting algorithms that are frequently used in image signal processing and summarize the performance evaluation. Based on this, we define an efficient algorithm when implemented in hardware among efficient sorting algorithms.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.46 no.4
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• pp.23-27
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• 2009

In this paper, we propose an effective compression method for electrocardiogram (ECG) signals. 1-D ECG signals are reconstructed to 2-D ECG data by period and complexity sorting schemes with image compression techniques to increase inter and intra-beat correlation. The proposed method added block division and mean-period normalization techniques on top of conventional 2-D data ECG compression methods. JPEG 2000 is chosen for compression of 2-D ECG data. Standard MIT-BIH arrhythmia database is used for evaluation and experiment. The results show that the proposed method outperforms compared to the most recent literature especially in case of high compression rate.

• Journal of The Korean Association of Information Education
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• v.13 no.2
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• pp.225-236
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• 2009

According to the revised guideline for information & communication technology, algorithm has to be dealt with the learning contents from elementary school, so now it needs to study various educational methods for students to learn algorithm easily and effectively. In this study, after selecting sort algorithms as the content of learning, which is recognized as an important part of algorithm, an playing activity-based algorithm teaching method and an animation-based algorithm learning and teaching method were applied for the lower graders of an elementary school. Sorting algorithm education is adopted in two different ways, then we got two conclusions after analyzing the results of a specially designed achievement test and the questionnaire. First, there were not great differences in both educational methods in academic achievement, but it was clear that the lower grade elementary students can learn algorithm with ease. Second, the playing activity-centered algorithm education is more effective than animation-based education in improving students' comprehension, interest and satisfaction.

• Journal of the Semiconductor & Display Technology
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• v.22 no.1
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• pp.72-77
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• 2023

In many manufacturing settings, including the semiconductor industry, products are completed by producing and assembling various components. Sorting out from randomly mixed parts and classification operations takes a lot of time and labor. Recently, many efforts have been made to select and assemble correct parts from mixed parts using robots. Automating the sorting and classification of randomly mixed components is difficult since various objects and the positions and attitudes of robots and cameras in 3D space need to be known. Previously, only objects in specific positions were grasped by robots or people sorting items directly. To enable robots to pick up random objects in 3D space, bin picking technology is required. To realize bin picking technology, it is essential to understand the coordinate system information between the robot, the grasping target object, and the camera. Calibration work to understand the coordinate system information between them is necessary to grasp the object recognized by the camera. It is difficult to restore the depth value of 2D images when 3D restoration is performed, which is necessary for bin picking technology. In this paper, we propose to use depth information of RGB-D camera for Z value in rotation and movement conversion used in calibration. Proceed with camera calibration for accurate coordinate system conversion of objects in 2D images, and proceed with calibration of robot and camera. We proved the effectiveness of the proposed method through accuracy evaluations for camera calibration and calibration between robots and cameras.

• 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.

• Journal of the Korean Society for Nondestructive Testing
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• v.35 no.1
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• pp.1-11
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• 2015

In this study, an online seed potato sorting system using a visible and near infrared (40 1100 nm) transmittance spectral technique and statistical model was evaluated for the nondestructive determination of infected and sound seed potatoes. Seed potatoes that had been artificially infected with Pectobacterium atrosepticum, which is known to cause a soil borne disease infection, were prepared for the experiments. After acquiring transmittance spectra from sound and infected seed potatoes, a determination algorithm for detecting infected seed potatoes was developed using the partial least square discriminant analysis method. The coefficient of determination($R^2_p$) of the prediction model was 0.943, and the classification accuracy was above 99% (n = 80) for discriminating diseased seed potatoes from sound ones. This online sorting system has good potential for developing a technique to detect agricultural products that are infected and contaminated by pathogens.