• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.8
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• pp.1819-1826
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• 2010

This paper proposes the image segmentation algorithm to extracts a fish object from a fish image for fish image retrieval. The conventional algorithm using gray level similarity causes wrong image segmentation result in the boundary area of the object and the background with similar gray level. The proposed algorithm uses the reinforced edge and the adaptive block-based threshold for the boundary area with weak contrast and the virtual object to improve the eroded or disconnected object in the boundary area without contrast. The simulation results show that the percentage of extracting the visual-fine object from the test images is under 90% in the conventional algorithm while it is 97.7% in the proposed algorithms.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.4C
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• pp.226-231
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• 2011

To improve the conventional illustrated fish book, this paper introduces the concept of an electronic illustrated fish book which applies IT techniques to the conventional one, and proposes the image retrieval for it. The image retrieval is a core technology of the electronic illustrated fish book and make it overwhelm the conventional one. Since fishes, even if the same kind, have different features in shape, color, and texture and the same fish can even have different features by its pose or environment at that time for taking a picture, the conventional image retrieval, that uses simple features in shape, color, and texture, is not suitable for the electronic illustrated fish book. The proposed image retrieval adopts detail shape features extracted from head, body, and tail of a fish and different weights are given to the features depending on their invariability. The simulation results show that the proposed algorithm is far superior to the conventional algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.10
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• pp.2108-2112
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• 2012

In this paper, we propose a method obtaining an improved panoramic image with forward warping transformation and bilinear interpolation in recovering information lost during the transforming process. The proposed fish-eyed image restructuring method is verified to be sufficiently effective in the experiment with various forms of fish-eyed lens images.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.5 s.305
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• pp.79-84
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• 2005

In this paper, we developed an omni-directional surveillance and motion detection method. The fish-eye lens provides a wide field of view image. Using this image, the equi-distance model for the fish-eye lens is applied to get the perspective and panorama images. Generally, we must consider the trade-off between resolution and field of view of an image from a camera. To enhance the resolution of the result images, some kind of interpolation methods are applied. Also the moving edge method is used to detect moving objects for the object tracking.

• Journal of the Korea Society of Computer and Information
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• v.13 no.4
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• pp.97-103
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• 2008

This study is to present a fainting motion recognizing method by using fish-eye lens images to sense emergency situations. The camera with fish-eye lens located at the center of the ceiling of the living room sends images, and then the foreground pixels are extracted by means of the adaptive background modeling method based on the Gaussian complex model, which is followed by tracing of outer points in the foreground pixel area and the elliptical mapping. During the elliptical tracing, the fish-eye lens images are converted to fluoroscope images. the size and location changes, and moving speed information are extracted to judge whether the movement, pause, and motion are similar to fainting motion. The results show that compared to using fish-eye lens image, extraction of the size and location changes. and moving speed by means of the conversed fluoroscope images has good recognition rates.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.601-605
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• 2009

Due to the fact that fish-eye lens can provide super wide angles with the minimum number of cameras, field-of-view over 180 degrees, many vehicles are attempting to mount the camera system. Camera calibration should be preceded, and geometrical correction on the radial distortion is needed to provide the images for the driver's assistance. However, vehicle fish-eye cameras have diagonal output images rather than circular images and have asymmetric distortion beyond the horizontal angle. In this paper, we introduce a camera model and metric calibration method for vehicle cameras which uses feature points of the image. And undistort the input image through a perspective projection, where straight lines should appear straight. The method fitted vehicle fish-eye lens with different field of views.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.1
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• pp.39-46
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• 2019

In this study, before system development for the elimination of foreign fish species, we propose an algorithm to classify fish species by training fish images with CNN. The raw data for CNN learning were directly captured images for each species, Dataset 1 increases the number of images to improve the classification of fish species and Dataset 2 realizes images close to natural environment are constructed and used as training and test data. The classification performance of four CNNs are over 99.97% for dataset 1 and 99.5% for dataset 2, in particular, we confirm that the learned CNN using Data Set 2 has satisfactory performance for fish images similar to the natural environment. And among four CNNs, AlexNet achieves satisfactory performance, and this has also the shortest execution time and training time, we confirm that it is the most suitable structure to develop the system for the elimination of foreign fish species.

• Journal of Advanced Navigation Technology
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• v.27 no.6
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• pp.877-883
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• 2023

For safe operation of ships and management of marine fisheries farms, the data set that extracts the boundaries of marine fisheries farms can provide information on obstacles in the vessel's navigation path in advance by examining whether it matches the fishing ground permit area. In addition, it can be used to determine whether fish farms are operating to compensate for damage caused by marine accidents, and the relevant local government can use it to manage fishing grounds. It is also highly utilized as basic data to identify obstacles for safe navigation of ships. In this study, Sentinel-2 satellite image data from the European Space Agency (ESA) was used to extract the boundaries of fish farms. From the video image, the fish farm's status data by cycle was divided into five zones: Busan-Ulsan area, Geoje-Changwon area, Goseong-Tongyeong area, and Namhae-Sacheon area. Through the image highlighting process, the farm boundary data and meta data were processed and extracted.

• Journal of Advanced Marine Engineering and Technology
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• v.32 no.6
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• pp.989-996
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• 2008

Recently, a few types of fish-cage in open sea are researched. This fish-cage has to operate monitoring system for keeping an optimum living condition for fish. The most efficient monitoring system is WVMS(Wireless Vision Monitoring System) for fish-cage in open sea. WVMS should be able to transmit video signal and communicate with each controller. So. it needs to be based on WLAN(Wireless LAN) which has characteristic of higher transfer-rate, In this paper, we propose a structure of WVMS using WLAN equipments for maritime environment and prove its effectiveness. We present the propagation loss model of WVMS's communication channel. measured by field test, and discuss its validity compared with the predictive value based on the Friss propagation model and Plane earth reflection model. We present the number of frames that is received from WLAN modem connecting with underwater-camera in field test spots. As a result, we confirmed that proposed WVMS is suitable for maritime environment and it is possible to be applied to fish-cage in open sea on 'seogwipo'.

• The KIPS Transactions:PartB
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• v.16B no.2
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• pp.131-140
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• 2009

This paper presents a new algorithm to the segmentation of the FISH images. First, for segmentation of the cell nuclei from background, a threshold is estimated by using the gaussian mixture model and maximizing the likelihood function of gray value of cell images. After nuclei segmentation, overlapped nuclei and isolated nuclei need to be classified for exact nuclei analysis. For nuclei classification, this paper extracted the morphological features of the nuclei such as compactness, smoothness and moments from training data. Three probability density functions are generated from these features and they are applied to the proposed Bayesian networks as evidences. After nuclei classification, segmenting of overlapped nuclei into isolated nuclei is necessary. This paper first performs intensity gradient transform and watershed algorithm to segment overlapped nuclei. Then proposed stepwise merging strategy is applied to merge several fragments in major nucleus. The experimental results using FISH images show that our system can indeed improve segmentation performance compared to previous researches, since we performed nuclei classification before separating overlapped nuclei.