• Korean Journal of Remote Sensing
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• v.27 no.1
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• pp.9-15
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• 2011

Since PAN(panchromatic) and MS(multispectral) imagery of pushbroom scanner have the offset between PAN and MS CCD(charge coupled device) in the focal plane, PAN and MS images are acquired at different time and angle. Since clouds are fast moving objects, they should lead mis-registration problem with wrong matching points on clouds. The registration of cloudy imagery to recognize and remove the contamination of clouds can be categorized into three classes: (1) cloud is considered as nose and removed (2) employing multi-spectral imagery (3) using multi-temporal imagery. In this paper, method (1) and (3) are implemented and analysed with cloudy pushbroom scanner images.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.36C no.12
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• pp.90-97
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• 1999

Recently, there have been many researches to automate processing and analysing image data in medical field, due to the advance of image processing techniques, the fast communication network and high performance hardware. In this paper, we design and implement the system based on the multi-layer neural network model to be able to analyze, differentiate and count blood cells in the peripheral blood image. To do these, we segment red and white-blood cell in blood image acquired from microscope with CCD(Charge-coupled device) camera and then apply the various feature extraction algorithms to classify. In addition to, we reduce multi-variate feature number using PCA(Principle Component Analysis) to construct more efficient classifier. So, in this paper, we are sure that the proposed system can be applied to a pathological guided system.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2012.07a
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• pp.40-43
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• 2012

3차원 영상 기술은 방송, 영화, 게임, 의료, 국방 등 다양한 기존 산업들과 융합하며 새로운 패러다임을 형성하고 있으며, 고품질 및 고해상도의 3차원 영상 획득에 대한 필요성이 강조되고 있다. 이에 따라, 최근에는 3차원 입체 영상을 제작 하는 방법 중 하나인 2D-plus-Depth 구조에 대한 연구가 활발히 진행되고 있다. 2D-plus-Depth 구조는 Charge-Coupled Device(CCD) 센서 등을 이용한 일반 카메라와 깊이 카메라를 결합한 형태로써 이 구조로부터 얻은 깊이 영상의 해상도를 상향 변환하기 위해서 Joint Bilateral Upsampling(JBU)[1], 컬러 영상의 정보를 활용한 보간법[2] 등의 방법들이 사용된다. 하지만 이 방법들은 깊이 영상을 높은 배율로 상향 변환할 경우 텍스처가 복사되거나 흐림 및 블록화 현상이 발생하는 문제점이 있다. 본 논문에서는 2D-plus-Depth 구조에서 얻은 고해상도 컬러 영상에서 보간 정보를 구하고 이 정보를 저해상도의 깊이 영상에 적용하여 상향 변환된 가이드 깊이 영상을 제작한다. 이 가이드 깊이 영상을 Bilateral Filtering[8]을 이용함으로써 고품질의 고해상도 깊이 영상을 획득한다. 실험 결과 제안하는 방법으로 해상도를 상향 변환을 할 경우에 기존의 보간법들에 비해 깊이 영상의 특성을 잘 보존함을 확인할 수 있고, 가이드 깊이 영상에 필터링을 처리한 결과가 JBU의 결과보다 향상됨을 확인할 수 있다.

• Smart Structures and Systems
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• v.12 no.3_4
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• pp.363-379
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• 2013

Dynamic displacement of structures is an important index for in-service structural condition and behavior assessment, but accurate measurement of structural displacement for large-scale civil structures such as long-span bridges still remains as a challenging task. In this paper, a vision-based dynamic displacement measurement system with the use of digital image processing technology is developed, which is featured by its distinctive characteristics in non-contact, long-distance, and high-precision structural displacement measurement. The hardware of this system is mainly composed of a high-resolution industrial CCD (charge-coupled-device) digital camera and an extended-range zoom lens. Through continuously tracing and identifying a target on the structure, the structural displacement is derived through cross-correlation analysis between the predefined pattern and the captured digital images with the aid of a pattern matching algorithm. To validate the developed system, MTS tests of sinusoidal motions under different vibration frequencies and amplitudes and shaking table tests with different excitations (the El-Centro earthquake wave and a sinusoidal motion) are carried out. Additionally, in-situ verification experiments are performed to measure the mid-span vertical displacement of the suspension Tsing Ma Bridge in the operational condition and the cable-stayed Stonecutters Bridge during loading tests. The obtained results show that the developed system exhibits an excellent capability in real-time measurement of structural displacement and can serve as a good complement to the traditional sensors.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.37 no.3
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• pp.293-300
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• 2009

The rotorcraft-based unmanned aerial vehicle(UAV) capable of performing close-range surveillance and reconnaissance has been developed. Trade studies on mission feasibility led to the adoption of a coaxial rotorcraft with twin rotors counter-rotating in one axis and driven by electric motors. A commercial off-the-shelf flight control computer(FCC) and a radio frequency modem were adopted for autonomous navigation. In order to achieve an aerial view, commercial charge-coupled device camera was also integrated into the vehicle. The performance of the completed vehicle was proved with manual flight test, and mission capability was verified through waypoint navigation flight after being equipped with FCC. This paper treats the whole process of design and system integration for development of the coaxial rotorcraft UAV.

• Korean Journal of Remote Sensing
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• v.18 no.6
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• pp.337-344
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• 2002

In general, in order to obtain position information from satellite images, satellite sensor model which represents the geometric relationship between sensor and targeted area should be established in the first place. However, it is not simple for modelling pushbroom satellite sensor due to the image capturing process. In recent development of new generation imaging sensors, a generic sensor model, which is applicable to all types of sensors such as frame, pushbroom, whiskbroom, and SAR is in great need to the remote sensing and photogrammetry community. In this paper, the RFM as sensor model was implemented with KOMPSAT EOC and SPOT satellite images and analyzed in cases where the number and distribution of ground control points were varied. The test results of RFM were presented and compared with those of Direct Linear Transformation(DLT).

• Korean Journal of Agricultural Science
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• v.47 no.4
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• pp.753-767
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• 2020

The commercial value of strawberries is affected by various factors such as their shape, size and color. Among them, size determined by weight is one of the main factors determining the quality grade of strawberries. In this study, image technology was developed to predict the weight of strawberries using the shape characteristics of strawberry cultivars. For realtime weight measurements of strawberries in transport, an image measurement system was developed for weight prediction with a charge coupled device (CCD) color camera and a conveyor belt. A strawberry weight prediction algorithm was developed for three cultivars, Maehyang, Sulhyang, and Ssanta, using the number of pixels in the pulp portion that measured the strawberry weight. The discrimination accuracy (R2) of the weight prediction models of the Maeyang, Sulhyang and Santa cultivars was 0.9531, 0.951 and 0.9432, respectively. The discriminative accuracy (R2) and measurement error (RMSE) of the integrated weight prediction model of the three cultivars were 0.958 and 1.454 g, respectively. These results show that the 2D imaging technology considering the shape characteristics of strawberries has the potential to predict the weight of strawberries.

• Smart Structures and Systems
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• v.33 no.1
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• pp.55-64
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• 2024

This paper proposes a fusion imaging-based coating-defect classification method for steel structures that uses zero-shot learning. In the proposed method, a halogen lamp generates heat energy on the coating surface of a steel structure, and the resulting heat responses are measured by an infrared (IR) camera, while photos of the coating surface are captured by a charge-coupled device (CCD) camera. The measured heat responses and visual images are then analyzed using zero-shot learning to classify the coating defects, and the estimated coating defects are visualized throughout the inspection surface of the steel structure. In contrast to older approaches to coating-defect classification that relied on visual inspection and were limited to surface defects, and older artificial neural network (ANN)-based methods that required large amounts of data for training and validation, the proposed method accurately classifies both internal and external defects and can classify coating defects for unobserved classes that are not included in the training. Additionally, the proposed model easily learns about additional classifying conditions, making it simple to add classes for problems of interest and field application. Based on the results of validation via field testing, the defect-type classification performance is improved 22.7% of accuracy by fusing visual and thermal imaging compared to using only a visual dataset. Furthermore, the classification accuracy of the proposed method on a test dataset with only trained classes is validated to be 100%. With word-embedding vectors for the labels of untrained classes, the classification accuracy of the proposed method is 86.4%.

• Journal of the Korean Society of Radiology
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• v.12 no.3
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• pp.435-441
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• 2018

In this study, we performed to design an image guiding algorithm to improve the efficiency and safety of treatment of varicose vein by focused ultrasound. The algorithm was suggested by different guiding images according to the location of varicose veins. In the case of deep-seated varicose veins, the target area was marked on the surface of the blood vessel in the obtained cross-sectional blood vessel ultrasound image. In the case of the superficial varicose vein, A guiding system based on image segmentation algorithm of the vascular region was suggested and designed two different algorithms according to varicose veins progression degree. as a results, the algorithm based on ultrasound image show a small error with $830{\mu}m$ at maximum. However, the algorithm based on charge coupled device image has a maximum error of 8.3 mm in some data. Therefore, it is expected that additional study is needed for superficial varicose vein image guiding algorithm, and it is expected that the accuracy of blood vessel tracking should be evaluated by constructing simple system.

• Journal of the Korean Society of Marine Environment & Safety
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• v.13 no.4
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• pp.55-63
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• 2007

The Group Digital Surveillance System for Fishery Safety and Security (GDSS-F2S) is to provide the target tracking information and the target identification information in order to secure an huge aquaculture farm-field from a thief. The two information, however, is not enough to indict the thief due to the lack of lawful evidences for the crime actions. To overcome this problem, we consider the target image information as one of solutions after discussion with the effective countermeasure tools for the crime actions with scenario-based analysis according to the geological feature of aquaculture farm-field. To capture the real-time image for the trespassing targets in the aquaculture farm-field area, we developed the image capture system which is consists of ultra sensitive CCD(Charge-Coupled Device) camera with 0.0001 Lux and supplementary devices. As results from the field tests for GDSS-F2S with image capture system, the high definite images of the vehicle number plate and shape, person's actions and features are obtainable not only day time but also very dark night without moon light. Thus it is cleary known that the improved GDSS-F2S with image capture system can provide much enough lawful evidences for the crime actions of targets.