• Journal of the Korean Society of Environmental Restoration Technology
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• v.24 no.6
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• pp.89-96
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• 2021

In this study, a deep-learning image analysis model was established and validated for AI-based monitoring of the tidal flat ecosystem for marine protected creatures Ocypode stimpsoni and their habitat. The data in the study was constructed using an unmanned aerial vehicle, and the U-net model was applied for the deep learning model. The accuracy of deep learning model learning results was about 0.76 and about 0.8 each for the Ocypode stimpsoni and their burrow whose accuracy was higher. Analyzing the distribution of crabs and burrows by putting orthomosaic images of the entire study area to the learned deep learning model, it was confirmed that 1,943 Ocypode stimpsoni and 2,807 burrow were distributed in the study area. Through this study, the possibility of using the deep learning image analysis technology for monitoring the tidal ecosystem was confirmed. And it is expected that it can be used in the tidal ecosystem monitoring field by expanding the monitoring sites and target species in the future.

• Journal of Ocean Engineering and Technology
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• v.31 no.1
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• pp.60-68
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• 2017

In this study, we analyzed the real time video image obtained from the video monitoring system to grasp the shoreline, beach width, and area change of Haeundae beach. The video monitoring techniques enabled continuous monitoring for a long period at a much lower cost than general survey methods. It was possible to grasp quantitative beach variation characteristics of Haeundae beach through image acquisition, rectification, and image processing of video images. According to the monitoring results, the erosion rate of Haeundae beach in spring and summer was -19.8% in 2014 and -6.7% in 2015. The erosion rate in 2016 was -6.4%, which showed that the erosion rate in spring and summer continued to decrease. In particular, the influence of the erosion at the time of typhoon CHABA was revealed to be smaller than in the past. It can be concluded that these variations were due to beach width expansion by beach nourishment and the installation of submerged breakwaters.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.10 no.1
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• pp.45-53
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• 1998

Video monitoring techniques and their applications to beaches were reviewed. The recent development of video hardware and image process made it possible to measure shoreline changes, sandbar morphology, wave runup, swash motion, and so on using video camaras. Especially, quantitative information from the video image can be obtained by digitization of image, rectification procedure, and image process. Using video monitoring techniques, measurements can be made at much lower cost and for long periods of time compared to the traditional measurement techniques, although these techniques are of lower accuracy and provide only indirect information on the land and water surface.

• Journal of Korea Multimedia Society
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• v.25 no.4
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• pp.583-599
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• 2022

Although the object detection accuracy with a single image has been significantly improved with the advance of deep learning techniques, the detection accuracy for pig monitoring is challenged by occlusion problems due to a complex structure of a pig room such as food facility. These detection difficulties with a single image can be mitigated by using a video data. In this research, we propose a method in pig detection for video monitoring environment with a static camera. That is, by using both image processing and deep learning techniques, we can recognize a complex structure of a pig room and this information of the pig room can be utilized for improving the detection accuracy of pigs in the monitored pig room. Furthermore, we reduce the execution time overhead by applying a pruning technique for real-time video monitoring on an embedded board. Based on the experiment results with a video data set obtained from a commercial pig farm, we confirmed that the pigs could be detected more accurately in real-time, even on an embedded board.

• Journal of Biosystems Engineering
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• v.31 no.5 s.118
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• pp.436-442
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• 2006

This research was conducted to design and develop a wired monitoring system for judging if sick or dead layers (SDL) exist in multi-tier layers battery (MLB) by machine vision, and to analyze its performance. In this study, 20 Brown Leghorn (Hi-Brown) layers aged 37 weeks old, were used as the experimental animals. The intensity of concern paid by layers on feed was over 90% during 5 minutes and 30 seconds after providing feed, and normal layers (NL) had been standing to take feed for that period. Therefore, in this study, the optimal judging time was set by this test result. The wired monitoring system developed was consisted of a driving device for carrying machine vision systems, a control program, a RS232 to RS485 convertor, an automatic positioning system, and an image capture system. An image processing algorithm was developed to find SDL in MLB by the processes of binary processing, erosion, expansion, labeling, and reckoning central coordinate of the captured images. The optimal velocity for driving unit was set up as 0.13 m/s by the test results for wired monitoring system, and the proximity switch was controlled not to be operated for 1.0 second after first image captured. The wired monitoring system developed was tested to evaluate the remote monitoring performance at lab-scale laying hen house. Results showed that its judgement success.ate on normal cage (without SDL) was 87% and that on abnormal cage (with SDL) was 90%, respectively. Therefore, it would be concluded that the wired monitoring system developed in this study was well suited to the purpose of this study.

• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.2184-2189
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• 2009

China is one of the countries in which flood occurs most frequently in the world and with the current economic growth; flood disaster causes more and more economic losses. Chinese government pays more attention to flood monitoring and assessment by space technology. Since1983, NOAA(AVHRR), Landsat-TM, LANDSAT-ETM+, JERS-1, SPOT, ERS-2, Radarsat-1, CBERS-1, Envisat have been used for flood monitoring and assessment. Due to the bad weather conditions during flood, microwave remote sensing is the major tools for flood monitoring. Envisat is one of the best satellite with powerful SAR. Its application for flood monitoring has been studied and its near real time(NRT) application can be realized on the basis of real-time delivery of image. During the 2005, 2006 and 2007 flood seasons, over the 31 NRT flood monitoring based on Envisat, had been carried out in Yangtze, Songua, Huaihe, pearl river basin. The result shows that Envisat SAR is very useful data source for flood disaster monitoring and assessment.

• IEMEK Journal of Embedded Systems and Applications
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• v.5 no.2
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• pp.46-56
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• 2010

This study proposes a monitoring system by cooperating the image information and the sensor information in a sensor network system. The monitoring system proposed in this study is divided into internal spaces, such as offices and laboratories, and external spaces including other various spaces. In the internal spaces, motions in objects are detected through cameras while some peripherals like lights are controlled by analyzing some temperature, humidity, and illuminance data detected by sensor nodes. In the external spaces, it is to watch certain intruders to the internal spaces through the interested region for exceptional time by installing cameras, motion detectors, and body detectors in such interested regions. In the results of the test that was applied to a practically limited environment by implementing some interfaces for the proposed system, it was considered that it is possible to watch surroundings effectively using the image information obtained from cameras and sensor information acquisited from sensor nodes.

• Tribology and Lubricants
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• v.23 no.6
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• pp.301-305
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• 2007

The wear particle analysis has been known as very effective method to foreknow and decide a moving situation and a damage of machine parts by using the digital computer image processing. But it was not laid down and trusted to calculate shape parameters of wear particle and wear volume. In order to apply image processing method in the foreknowledge and decision of lubricated condition, it needs to verify the reliability of the calculated data by the image processing and to lay down the number of images and the amount of wear particle in one image. In this study, the lubricated friction experiment was carried out in order to establish the optimum image capture with the SM45C specimen under experiment condition. The wear particle data were calculated differently according to the number of image and the amount of wear particle in one image.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.53-56
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• 2008

Generally, the quality of satellite images is expressed by GSD (Ground Sample Distance), MTF (Modulation Transfer Function) and SNR (Signal to Noise Ratio). However, these factors are technology-oriented and do not explain interpretability of satellite images. We need a standardized index which shows standard of interpretability. In this study, we estimated NIIRS (National Imagery Interpretability Rating Scale) through the GIQE (General Image Quality Equation) which is able to judge image interpretability with the standardized index. Traditionally, NIIRS has been determined manually by specialized image analysts. We used the GIQE in order to reduce inefficiency and high costs cause by manual interpretation and to produce accurate NIIRS. For monitoring image degradation, we estimated GIQE physical parameters from image analysis and carried out time series analysis about the quality of the KOMPSAT-1 images. On all of the tests, we were able to identify the image degradation due to the changing time. This indicates that NIIRS derived from GIQE will be used for image degradation indicator.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.499-502
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• 2003

Increase energy costs have placed demands for improved combustion efficiency, high equipment availability, low maintenance and safe operation. Simultaneously low NOx modification, installed due to stricter environmental legislation, require very careful combustion management. We aimed at gaining the relationship between burner flame image and emissions such as NOx and unburned carbon in furnace by utilizing the image processing method. For the first step of development, its possibility test was undertaken with bench furnace. The test proceeded to the second step with pilot furnace, the system was observed to be effective for evaluating the combustion conditions. By using this technology, it is possible to perform continuous monitoring of the combustion conditions and instant detection of individual changes for each burner to prevent future loss of ignition.