• 한국어병학회지
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• 제35권2호
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• pp.205-214
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• 2022

In recent years, there have been many studies investigating changes in animal behavior using video tracking technology to track motion. However, there have been very few studies and results on changes in the behavior of fish infected with a pathogen. Therefore, the present study attempted to analyze the behavior of angelfish (Pterophyllum scalare) infected with bacterial pathogens using video tracking. Two cameras were placed in front of the water tank to obtain behavior data, and tracking was performed for three days until the day of death. Data such as average speed, changes in speed, the locations of the fish in the tank, and fractal dimension were statistically analyzed based on the fish speed and location in the tank of the fish. For bacterial infection, an individual angelfish was intraperitoneally injected with approximately 10⁶ CFU ml^-1 of Aeromonas hydrophila or Edwardsiella piscicida. The experiment was carried out five times for each group. Fish infected with the bacterial pathogens showed a tendency to increase in speed and to spend more time in the upper part of the tank one or two days before death. On the day the fish died, the average speed, changes in speed, and the fractal dimension value were significantly lower than the corresponding values in the control group, and the fish also remained in the lower part of the tank. Our results indicated that behavioral changes in fish could be successfully detected earlier than death using video tracking technology, and that this method presents potential for disease monitoring in aquaculture.

• IEIE Transactions on Smart Processing and Computing
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• 제5권6호
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• pp.375-382
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• 2016

This paper realizes control of the motion of a swimming robot fish in order to implement an underwater robot fish aquarium. And it implements positional control of a two-axis trajectory path of the robot fish in the aquarium. The performance of the robot was verified though certified field tests. It provided excellent performance in driving force, durability, and water resistance in experimental results. It can control robot motion, that is, it recognizes an object by using an optical flow object-detecting algorithm, which uses a video camera rather than image-detecting sensors inside the robot fish. It is possible to find the robot's position and control the motion of the robot fish using a radio frequency (RF) modem controlled via personal computer. This paper proposes realization of robot fish motion-tracking control using the optical flow object-detecting algorithm. It was verified via performance tests of lead-lag action control of robot fish in the aquarium.

• 한국전자통신학회논문지
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• 제5권1호
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• pp.102-108
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• 2010

컴퓨터 그래픽스 기술을 접목한 디지털 영상 콘텐츠 산업이 점차 증가하면서, 사용자들은 현실세계와 흡사할 정도의 고품질 애니메이션을 요구하고 있으며, 사이버수족관 및 어류백과사전 등을 통해서 어류의 형태나 유영방식을 관찰하고자 한다. 본 연구에서는 해저 환경을 표현함에 있어서 가장 핵심이 되는 어류의 자연스럽고도 역동적인 움직임을 표현하기 위해 어류 성장 과정 시스템을 설계하고 개발하였다. 본 시스템에서는 기존 어류 유영 방식을 새롭게 보완한 알고리즘을 사용한 시뮬레이션과 기존 모핑 연구에서 제시되지 않은 새로운 모핑 기법을 제안한다. 또한 어류의 성장 과정 중 환경 요인에 따라 발생하는 질병 감염 상태를 현실적으로 표현한다. 기존 어류 연구와 다르게 포괄적인 어류 연구를 진행하여 어류에 관련된 전반적인 특징을 현실적으로 시뮬레이션 하여 살펴보게 된다.

• Fisheries and Aquatic Sciences
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• 제14권3호
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• pp.218-225
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• 2011

Dual frequency identification sonar (DIDSON) is an imaging sonar that has been used for numerous fisheries investigations in a diverse range of freshwater and marine environments. The main purpose of DIDSON is fish counting, fish sizing, and fish behavioral studies. DIDSON records video-quality data, so processing power for handling the vast amount of data with high speed is a priority. Therefore, a semiautomated analysis of DIDSON data for fish counting, sizing, and fish behavior in Echoview (fisheries acoustic data analysis software) was accomplished using testing data collected on the Rakaia River, New Zealand. Using this data, the methods and algorithms for background noise subtraction, image smoothing, target (fish) detection, and conversion to single targets were precisely illustrated. Verification by visualization identified the resulting targets. As a result, not only fish counts but also fish sizing information such as length, thickness, perimeter, compactness, and orientation were obtained. The alpha-beta fish tracking algorithm was employed to extract the speed, change in depth, and the distributed depth relating to fish behavior. Tail-beat pattern was depicted using the maximum intensity of all beams. This methodology can be used as a template and applied to data from BlueView two-dimensional imaging sonar.

• 한국어병학회지
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• 제1권2호
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• pp.73-76
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• 1988

There prevailed lymphocystis disease with 1 to 2cm in size in the skin and pins of cultured Sebastes schlegeli in fish farms in Tongyoung-gun, Sanyang-myeon, Kon-ri from summer, 1987 to fall, 1988. Though there were some difference between each fish farm, this disease prevailed widely from immature fish to mature fish, less than 10cm to 30cm in body length with about 8 through 80% of infection rate. Sebastes schlegeli with the lymphocystis disease showed combined nipple-shaped mass by doubly, triply propagated lymphocystis. But the author considered that lymphocystis disease was not a direct cause of death of Sebastes schlegeli, the fish showed marked inflammation by seconary infection of pathogenic organisms.

• 수산경영론집
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• 제48권2호
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• pp.53-66
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• 2017

More than 90% of cultured fish is consumed by sliced raw fish which is usually an eating out menu in South Korea. In order to develop the aquaculture industry in Korea, It is very important to know whether consumers can differentiate each species or not and how consumers recognize each species by certain criteria. for example taste, seasonal preference. The purpose of this study is to understand the competitive relationship through positioning studies of each species by the selection attributes. A total of 221 consumers were surveyed in korea. This study adapted multidimensional scaling(MDS) analysis to explore how consumers position sliced raw fish species based on selection attributes. This study has produced perceptual maps of sliced raw fish market. Empirical data was collected from sliced raw fish consumers in Korea. The results of MDS analysis reveal that 7 species are divided into 3 groups(flat fish, black rock fish), (red sea bream, salmon, tuna), (sea bass, gray mullet). In this study flat fish and black rock fish are perceived as safe, familiar, good value species. Red seabream, salmon, tuna are perceived as luxurious species. Sea bass and gray mullet are perceived as unfamiliar species.

• 수산경영론집
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• 제38권1호
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• pp.19-45
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• 2007

There have not been many studies which considered both quantitative and qualitative location factors on the issues of site selection problems for a fish farm. This study develops AHP(analytic hierarchy process) model to resolve site selection problem for a fish raising farm by using quantitative and qualitative factors. In order to evaluate the validity of the location factors found in the literature review, the study used advice from fish raising farmers and related academic experts. Four major factors have been selected as economic factors, social factors, natural environmental factors and infrastructures. An AHP structural diagram has developed by considering the factors and potential sites proposed for fish farming. Through the survey on the preference of factors and potential sites, pairwise comparison matrices have been estimated and used to calculated the relative weights of each potential site. The AHP model process shown in the study can be applied to resolve site selection problems for fish raising farmers.

• 한국수산과학회지
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• 제55권5호
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• pp.638-644
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• 2022

The measurement of morphological features is essential in aquaculture, fish industry and the management of fishery resources. The measurement of fish requires a large investment of manpower and time. To save time and labor for fish measurement, automated and reliable measurement methods have been developed. Automation was achieved by applying computer vision and machine learning techniques. Recently, machine learning methods based on deep learning have been used for most automatic fish measurement studies. Here, we review the current status of automatic fish measurement with traditional computer vision methods and deep learning-based methods.

• Fisheries and Aquatic Sciences
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• 제26권12호
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• pp.698-707
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• 2023

Fish are an essential resource in human society, and while ecological research on them is challenging, it is absolutely necessary. Recent technologies enabled researchers to monitor underwater fish behavior. Acoustic signals, satellite-mediated location estimation, and light-based geolocation are powerful tools for tracking fish movements from freshwater to deep-sea habitats. These tools allow us to track various fish species and elucidate their ecology. Furthermore, based on these technologies, we can develop fisheries management plans and enhance aquaculture productivity. In this review, we also discuss challenges in improving current technologies and provide future recommendations for fish bio-logging studies.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2015년도 추계학술발표대회
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• pp.1341-1344
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• 2015

In this paper, the designed fish robot is researched and developed for aquarium underwater robot. This paper is a study on how the outside technology merely to find the location of fish robots without specific sensor or internal devices. This model is designed to detect the position of the Robotic Fish in the Mat lab and Simulink. This intends to recognize the shape of the tank via a video device such as a camera or camcorder using an image processing technique to identify the location of the robotic fishes. Here, we are applied the two methods, one is Hom - Schunk Method and second one is newly proposed method that is the comparing image data algorithm. The Horn - Schunck Method is used to obtain the velocity for each pixel in the image and the comparing image data algorithm is proposed to obtain the position with comparing two video frames and assumes a constant velocity in each video frame.