• Title/Summary/Keyword: fish image

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Enhancing Red Tide Image Recognition using NMF and Image Revision (NMF와 이미지 보정을 이용한 적조 이미지 인식 향상)

  • Park, Sun;Lee, Seong-Ro
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.16 no.2
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    • pp.331-336
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    • 2012
  • Red tide is a temporary natural phenomenon involving harmful algal blooms (HABs) in company with a changing sea color from normal to red or reddish brown, and which has a bad influence on coast environments and sea ecosystems. The HABs have inflicted massive mortality on fin fish and shellfish, damaging the economies of fisheries for almost every year from 1990 in South Korea. There have been many studies on red tide due to increasing damage from red tide on fishing and aquaculture industry. However, internal study of automatic red tide image classification is not enough. Especially, extraction of matching center features for recognizing algae image object is difficult because over 200 species of algae in the world have a different size and features. Previously studies used a few type of red tide algae for image classification. In this paper, we proposed the red tide image recognition method using NMF and revison of rotation angle for enhancing of recognition of red tide algae image.

Anal Fin Deformity in the Longfin Trevally, Carangoides armatus (R$\ddot{u}$ppell, 1830) Collected from Nayband, Persian Gulf

  • Jawad, Laith;Sadighzadeh, Zahra;Salarpouri, Ali;Aghouzbeni, Seyed
    • Korean Journal of Ichthyology
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    • v.25 no.3
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    • pp.169-172
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    • 2013
  • A malformation of the anal fin in longfin trevally, Carangoides armatus, is described and compared with normal specimens. The fish specimen is clearly shown anal fin deformity with missing of 3 spines and 6 rays. The remaining eleven anal fin rays are shorter than those in the normal specimen. The causative factors of this anomaly were discussed.

A Study on Fish Tracking Using The Effective Background Image (효과적인 배경이미지를 통한 물고기 추적 기법)

  • 강민경;강이철;김성우;차의영
    • Proceedings of the Korea Multimedia Society Conference
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    • 2000.11a
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    • pp.155-158
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    • 2000
  • 본 논문에서는 컴퓨터 비젼의 기술을 이용하여 생태학적인 실험을 위한 기반으로 물고기를 추적하는 방법을 보여준다. 특히 최적의 배경 이미지를 구하여서 그것을 바탕으로 차영상의 기법을 사용하여 인하는 물체(object), 여기서는 물고기만을 얻는다. 그리고 나서 기존의 신경회로망 기법인 ART2를 사용하여서 그 물고기의 영역을 클러스터링하여서 Object의 좌표를 획득한다. 배경이미지를 이용하여 배경을 제외한 object만 난은 영상을 얻는 방법은 기존의 연구에도 많다. 그러나 이 논문의 방식은 더욱더 그 물체의 윤곽을 뚜렷하게 나타내고, 간단한 방법을 소개하고 있다.

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Conversion of Fish Eye Image Using Scaling Function (스케일링 함수를 이용한 어안 영상 변환)

  • Kim, Tae-Woo
    • Proceedings of the KAIS Fall Conference
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    • 2008.11a
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    • pp.254-256
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    • 2008
  • 어안 영상은 화각이 일반 카메라 영상보다 큰 반면, 영상의 피사체 왜곡이 커서 사용자의 인지에 자연스럽지 못하다. 그래서 어안 영상은 원근 영상으로 변환하여 사용하는 것이 일반적이다. 본 논문에서는 스케일링 함수를 이용한 어안 영상의 원근 영상 변환 방법을 제안하였다. 특히 스케일링 함수를 적용한 결과 영상에서 크기 왜곡과 기하학적 왜곡을 감소되는 장점을 보였다.

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Comparative Study of Fish Detection and Classification Performance Using the YOLOv8-Seg Model (YOLOv8-Seg 모델을 이용한 어류 탐지 및 분류 성능 비교연구)

  • Sang-Yeup Jin;Heung-Bae Choi;Myeong-Soo Han;Hyo-tae Lee;Young-Tae Son
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.30 no.2
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    • pp.147-156
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    • 2024
  • The sustainable management and enhancement of marine resources are becoming increasingly important issues worldwide. This study was conducted in response to these challenges, focusing on the development and performance comparison of fish detection and classification models as part of a deep learning-based technique for assessing the effectiveness of marine resource enhancement projects initiated by the Korea Fisheries Resources Agency. The aim was to select the optimal model by training various sizes of YOLOv8-Seg models on a fish image dataset and comparing each performance metric. The dataset used for model construction consisted of 36,749 images and label files of 12 different species of fish, with data diversity enhanced through the application of augmentation techniques during training. When training and validating five different YOLOv8-Seg models under identical conditions, the medium-sized YOLOv8m-Seg model showed high learning efficiency and excellent detection and classification performance, with the shortest training time of 13 h and 12 min, an of 0.933, and an inference speed of 9.6 ms. Considering the balance between each performance metric, this was deemed the most efficient model for meeting real-time processing requirements. The use of such real-time fish detection and classification models could enable effective surveys of marine resource enhancement projects, suggesting the need for ongoing performance improvements and further research.

Research on Development of Side Scan Sonar using multi-beam Sensors (멀티빔 센서를 이용한 사이드 스캔 소나 개발에 관한 연구)

  • 장유신;계중읍;구융서;박승수;김지한;이만형
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2004.10a
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    • pp.696-699
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    • 2004
  • A side scan sonar system uses the towfish installed sonars, It is an equipment that search images of the bottom surface of the sea in real time. It is a typical equipment that is related to a sea investigation such as a geological survey, seabed communication cable and power line cable placing repair investigation, fish breeding ground investigation, sea purification, relic and mineral investigation, and mine and submarine search. It used to fined objects and investigate on the seabed surface. But, recently, it is used to sea purification and geological survey that require information of the correct surface of the seabed. So, it needs various filtering technique and image processing techniques development to acquire high resolution image. therefore, this research develops a side scan sonar using multi-beam sensors that supply various information with the fast scan speed and correct high resolution that is not a simple underwater investigation equipment.

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Study on Development of Side Scan Sonar Using Multi-beam Sensors (다중 빔 센서를 이용한 측면주사음탐기에 관한 연구)

  • Chang, Y.S.;Keh, J.E.;Park, S.S.;Lee, M.H.
    • Proceedings of the Korean Society of Marine Engineers Conference
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    • 2006.06a
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    • pp.317-318
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    • 2006
  • The towfish oi a side scan sonar is an equipment that search images of the bottom surface of the sea in real time. It is a typical equipment that is related to a sea investigation such as a geological survey, seabed communication cable and power line cable placing repair investigation, fish breeding ground investigation, sea purification, relic and mineral investigation, and mine and submarine search. It used to find objects and Investigate on the seabed surface. But, recently, it is used to sea purification and geological survey that require information of the correct surface of the seabed. So, it needs various filtering technique and image processing techniques development to acquire high resolution image. Therefore, this research develops a side scan sonar using multi-beam sensors that supply various information with the fast scan speed and correct high resolution that is not a simple underwater investigation equipment.

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Improvement of Ultrasound Images Using Motion Estimation and Recursive Filtering (Motion Estimation과 Recursive Filtering을 사용한 초음파 동화상의 개선)

  • Song, J.S.;Lee, J.K.;Yang, Y.J.;Choi, H.J.;Oh, C.H.
    • Proceedings of the KOSOMBE Conference
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    • v.1995 no.05
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    • pp.123-126
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    • 1995
  • The purpose of this paper is to improve ultrasound images using motion estimation and recursive filtering. Although averaging without motion correction can make image blurring, the proposed estimation method improves image SNR without motion blurring by recursively averaging images with motion correction. Computer simulation on the proposed method has been performed to improve phantom and ultrasound fish images and the results show the utility of the proposed method.

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Collision Avoidance Using Omni Vision SLAM Based on Fisheye Image (어안 이미지 기반의 전방향 영상 SLAM을 이용한 충돌 회피)

  • Choi, Yun Won;Choi, Jeong Won;Im, Sung Gyu;Lee, Suk Gyu
    • Journal of Institute of Control, Robotics and Systems
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    • v.22 no.3
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    • pp.210-216
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    • 2016
  • This paper presents a novel collision avoidance technique for mobile robots based on omni-directional vision simultaneous localization and mapping (SLAM). This method estimates the avoidance path and speed of a robot from the location of an obstacle, which can be detected using the Lucas-Kanade Optical Flow in images obtained through fish-eye cameras mounted on the robots. The conventional methods suggest avoidance paths by constructing an arbitrary force field around the obstacle found in the complete map obtained through the SLAM. Robots can also avoid obstacles by using the speed command based on the robot modeling and curved movement path of the robot. The recent research has been improved by optimizing the algorithm for the actual robot. However, research related to a robot using omni-directional vision SLAM to acquire around information at once has been comparatively less studied. The robot with the proposed algorithm avoids obstacles according to the estimated avoidance path based on the map obtained through an omni-directional vision SLAM using a fisheye image, and returns to the original path. In particular, it avoids the obstacles with various speed and direction using acceleration components based on motion information obtained by analyzing around the obstacles. The experimental results confirm the reliability of an avoidance algorithm through comparison between position obtained by the proposed algorithm and the real position collected while avoiding the obstacles.

Study on the Evaluation Factors of Seafood Purchase for School Food Service (학교급식 수산물구매에 영향을 미치는 제품평가요인)

  • Jang, Young-Soo;Park, Jeong-A
    • The Journal of Fisheries Business Administration
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    • v.40 no.2
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    • pp.1-25
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    • 2009
  • The major part of non-commercial food service is food service for school which has no any objective quality standards. Each school has different standard when they buy seafood for SFS(School Food Service). The research purpose is whether or not the extrinsic cues of the seafood such as price, the source origin, company image, safety standards, etc or the intrinsic cues such as fishy smell, the hardiness of fish meat, others have any effect on the seafood evaluation when school nutritionist purchase it, for more objective basis. The research method is distributing questionnaire survey through e-mail or directly visiting the schools from October 30 to November 9, 2007. The questionnaire was distributed to 70 nutritionists of food service for elementary school in Busan. Total 50 questionnaires are used as data in the statistical analysis using SPSS package software. The research results are; First, there is interaction effect between the extrinsic and intrinsic cues of seafood for SFS. That is when the school nutritionist valued on intrinsic cues of seafood such as a fishy smell, the hardiness of fish meat and etc influence on the extrinsic cues such as price, source origin, reliable circulation process, HACCP application, etc. Second, the extrinsic cues of the seafood give no effect on perceived quality. Since seafood for SFS are heavy buying, prearrangement contract and most of them using pre-treated frozen aquatics. Third, the intrinsic cues of the seafood give no effect on perceived quality. The extrinsic cues consist of 5 parts namely "opening about quality", "source origin", "company image", "safety/standards" and "price/package". However, "safety/standard" was the only affecting factor to perceive quality. The reason is that in fact they have no standards or any document proving the quality of the seafood unless safety standards factor. Last, the perceived quality is an important factor for perceived value and purchase intention. It is showed that there is a path to form a willing to buy through the perceived value after school nutritionist recognizes the perceived quality.

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