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장국렬,오성훈,김상미,박순영,방만원 木浦大學校 工業技術硏究所 1996 工業技術硏究誌 Vol.6 No.-
In this paper, we present an automatic PCB counting system which can automatically count the PCBs in assembling process and store the results in computer to be used as the data base of production managerment. The system is composed of optical sensors, a PC interface board, a PC and DB program. The optical sensors which are located at upside and downside of the PCB assembling line send the signal to the computer when the PCB is passing through the sensor position. The DB stored in the computer can be searched according to the production date or the PCB models. The experimental results show that the developed counting system can lead to the performance improvement of PCB assembling process by reduction of employes and automation of production management.
한석균,박순영,장국렬 木浦大學校 情報産業硏究所 1996 情報産業硏究誌 Vol.4 No.-
In this paper, we present an order statistics based edge detector which has good edge detection characteristics in the presence of Gaussian and impulsive noise. The developed edge detector combines an order statistic (OS) Laplacian operator which is designed to be robust with respect to noise, and a zero-crossing detector. The edge detector computes the second derivative of the image using the OS Laplacian operator and the zero-crossing detection is followed to locate the edge points.OS Laplacian operation is carried out from the difference of the outputs of a median filter and a modified trimmed mean(MTM) filter. The performance of the edge detector in the presence of Gaussian and impulsive noise is evaluated and compared to the performance of well established edge detectors such as a Laplacian of Gaussian(LoG) operator and a Sobel operator. Experimental results with both synthetic and real images show that the OS edge detector has the best edge detection characteristics in the presence of Gaussian and impulsive noise.
지능화된 무인감시시스템을 위한 침입자 추적 알고리즘에 관한 연구
장국렬,박순영 木浦大學校 情報産業硏究所 1997 情報産業硏究誌 Vol.5 No.-
In this paper, an effective moving object tracking algorithm which can detect motion of moving objects from the image sequences taken by a CCD camera and predict moving direction and velocity of moving objects is presented for an intelligent and unmanned surveillance system. First, the proposed algorithm detects moving objects and computes movements by applying a differential operation to the image frames. Secondly, the motion vector and center of a moving objects are measured by using 2-step block matching algorithm. Finally, the algorithmtracks an intruder by predicting moving direction and velocity from the accumulated motion vector. The computer simulation is carried out to analyze the performance of the proposed algorithm. The results show that the algorithm can track a walking man and a running man effectively.
무인감시시스템 구현을 위한 이동체 인식 알고리즘에 관한 연구
장국렬,방만원,박진홍,박순영 木浦大學校 情報産業硏究所 1996 情報産業硏究誌 Vol.4 No.-
In this paper, an effective algorithm which can detect moving objects from the image sequences and classify an intruder from other moving objects is presented for an implementation of unmanned surveillance system. The proposed algorithm uses a stick figure model for features of the moving object since the stick figure model can be represent the characteristics of the moving objects. The stick figure model is extracted by applying the thining algorithm to the binary difference image between the reference and the image of a moving object. The computer simulation is carried out to analyze the performance of the proposed algorithm. The results show that the algorithm can discriminate a moving person and a moving animal with high degree of reliability.
김으뜸(Eu-Tteum Kim),장국렬(Kug-Lyoul Jang),곽연숙(Yeon-Sook Kwak),이호성(Ho-Sung Lee),박선일(Son-Il Pak) 한국예방수의학회 2020 예방수의학회지 Vol.44 No.4
The current study explored the movement characteristics of 14 migratory bird species that wintered in the Republic of Korea between 2014 and 2020. The migratory bird movement information was obtained via a global positioning system operated by the Korean government. The velocity of movement, number of clusters, and size of clusters of the migratory bird species during their movement from their departing country to the Republic of Korea were estimated by applying a method based on density-based spatial clustering of applications with noise. The average movement velocity of pintails (Anas acuta) that departed from China or Russia was 32.77 km/h, the highest velocity among those measured for the 14 migratory bird species. The average number of clusters for cinereous vultures (Aegypius monachus) was 43.00, which was the largest cluster number observed. However, herring gulls (Larus argentatus) had the largest cluster area with an average cluster radius of 27.43 km while wintering in the Republic of Korea. The findings of the current study could be useful in increasing the effectiveness of the Korean national highly pathogenic avian influenza (HPAI) surveillance program. The human and material resources of the HPAI surveillance could be allocated after considering the results of this study, revealing the movement characteristics of wintering migratory birds in Korea. The HPAI surveillance program should include fecal or swab sampling to detect the HPAI virus in both pintail and bean goose (Anser faballis) wintering sites. Sampling of those sites should have a higher priority than that for other migratory bird wintering sites since pintail and bean goose move faster and form larger clusters.