• Nuclear Engineering and Technology
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• v.45 no.3
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• pp.361-366
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• 2013

An imaging technique to visualize the internal defects in a plate-type nuclear fuel specimen was developed by using an active optical interferometer for a nondestructive quality inspection. A periodic thermal wave having a sinusoidal intensity pattern induced a periodical strain variation for the specimen. The varying strain image was acquired using an optical laser interferometer. The strain distribution over the internal defects will be distorted in an acquired strain image because a part of the thermal wave will be reflected from these defects during propagation. In this paper, internal defects were efficiently visualized by sequentially accumulating the extracted defect components. The experimental results confirmed that the developed visualization system can be a valuable tool to detect the internal defects in plate-type nuclear fuel.

• Journal of the Korean institute of surface engineering
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• v.54 no.5
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• pp.278-284
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• 2021

Corrosion of steel plate is common phenomenon which results in the gradual destruction caused by a wide variety of environments. Corrosion monitoring is the tracking of the degradation progress for a long period of time. Corrosion on steel plate appears as a discoloration and any irregularities on the surface. In this study, we developed a quantitative evaluation method of the rust formed on steel plate by using k-means clustering from the corroded area in a given image. The k-means clustering for automated corrosion detection was based on the GrabCut segmentation and Gaussian mixture model(GMM). Image color of the corroded surface at cut-edge area was analyzed quantitatively based on HSV(Hue, Saturation, Value) color space.

• Journal of the Korean institute of surface engineering
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• v.54 no.2
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• pp.84-89
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• 2021

The visual inspection method is widely used for corrosion damage analysis of steel plate due to the cost-efficient, fast and reasonably accurate results. However, visual inspection of corrosion deteriorated degree has a problem that the reliability of results differs depending on the inspector's individual knowledge and experience. In this study, we evaluated the degree of corrosion from a given image by using image segmentation method based on the grabcut and HSV(Hue, Saturation, Value) color image processing techniques for the development of an automatic inspection tool. The code written in Python based OpenCV-python libraries was used to categorize the images.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.6 no.1
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• pp.6-17
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• 2013

Recently, the color of vehicle license plate has been changed from green to white. Thus the vehicle plate recognition system used for parking management systems, speed and signal violation detection systems should be robust to the both colors. This paper presents a vehicle license plate recognition system, which works on both of green and white plate at the same time. In the proposed system, the image of license plate is taken from a captured vehicle image by using morphological information. In the next, each character region in the license plate image is extracted based on the vertical and horizontal projection of plate image and the relative position of individual characters. Finally, for the recognition process of extracted characters, PCA(Principal Component Analysis) and LDA(Linear Discriminant Analysis) are sequentially utilized. In the experiment, vehicle license plates of both green background and white background captured under irregular illumination conditions have been tested, and the relatively high extraction and recognition rates are observed.

• International Journal of Precision Engineering and Manufacturing
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• v.4 no.5
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• pp.41-46
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• 2003

Electronic Speckle Pattern Interferometry (ESPI) has been recently developed and widely used because it has the advantage of being able to measure surface deformations of engineering components and materials in industrial areas without contact. The speckle patterns formed with interference and scattering phenomena can measure not only the out-of-plane but also the in-plane deformations. Digital image equipment processes the information included in the speckle patterns and displays the consequent interferogram on a computer monitor. In this study, the experimental results of a canti-levered plate using ESPI were compared with those obtained from the simple beam theory. The ESPI results of the canti-levered plate, analyzed by 4-step phase shifting method, are close to the theoretical expectation. Similarly, out-of-plane displacements of a spot welded canti-levered plate were also measured by ESPI with 4-step phase shifting technique. The phase map of the spot welded canti-levered plate is quite different from that of the canti-levered plate without spot welding.

• Journal of Intelligence and Information Systems
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• v.8 no.1
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• pp.15-25
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• 2002

This paper proposes a vehicle license plate recognition system, which has relatively a simple structure and is highly tolerant of noise, by using the DCT(Discrete Cosine Transform) coefficients extracted from the character region of a license plate and the LVQ(Learning Vector Quantization) neural network. The image of a license plate is taken from a captured vehicle image based on RGB color information, and the character region is derived by the histogram of the license plate and the relative position of individual characters in the plate. The feature vector obtained by the DCT of extracted character region is utilized as an input to the LVQ neural classifier fur the recognition process. In the experiment, 109 vehicle images captured under various types of circumstances were tested with the proposed method, and the relatively high extraction rate of license plates and recognition rate were achieved.

• Journal of Power System Engineering
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• v.5 no.1
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• pp.64-72
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• 2001

According to the regulation of IMO, oil discharge from ships is allowed under 15ppm only and an oil filtering equipment is essential. However, for large ships using heavy fuel oil of over S.G 0.98 and viscosity 380cSt and system oil, it has been in difficulty to process with existing filtering type of oily water separator. A parallel plate type oily water separator which is one of gravity type separators can be used as an assistant equipment for the oil filtering system to meet the present IMO standard of 15 ppm, because it is an efficient method in dealing with a large amount of rich oil with high specific gravity. This work is focused on the fundamental investigation of the performance of the plate type oily water separator by visualization method and PIV(Particle Image Velocimetry) measurement to acquire multi-point velocity data simultaneously. The experimental results showed that the space of the plates acts a significant role in separating process and it was found that an important point to minimize a vortex flow is to flow a large amount of fluid in space of the plates in order to promote the efficiency of separation.

• Journal of Korea Society of Digital Industry and Information Management
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• v.18 no.4
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• pp.1-11
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• 2022

Recently, research on license plate recognition, which is a core technology of an intelligent transportation system(ITS), is being actively conducted. In this paper, we propose a method to extract numbers and characters from low-quality license plate images by applying the YOLOv4 algorithm. YOLOv4 is a one-stage object detection method using convolution neural network including BACKBONE, NECK, and HEAD parts. It is a method of detecting objects in real time rather than the previous two-stage object detection method such as the faster R-CNN. In this paper, we studied a method to directly extract number and character regions from low-quality license plate images without additional edge detection and image segmentation processes. In order to evaluate the performance of the proposed method we experimented with 500 license plate images. In this experiment, 350 images were used for training and the remaining 150 images were used for the testing process. Computer simulations show that the mean average precision of detecting number and character regions on vehicle license plates was about 93.8%.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.3
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• pp.145-153
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• 2009

The purpose of this research is to propose a system to detect a strip defect on a iron plate using an image processing, one way of finding defects on an iron plate. An existing way of image processing is using a light source which release a light energy in a certain frequency and a light absorbing display which responds to the light source. This research attempts to detect defects by using a image processing and multi-Tread which handles an illumination, without depending on characteristics of light frequency. One of the advantages of this method is that it makes up for the weakness of the existing method which was too difficult for users to notice a defect. Also this method makes it possible to realize a real-time monitoring on a plate of iron. The other advantage of this method is that it reduces the price of hardwares on demand to match the frequency of light emitting display and light absorbing display because this method only needs a hardware which is easy to buy in any market.

• Journal of Korea Multimedia Society
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• v.8 no.11
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• pp.1496-1509
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• 2005

In this paper, an adaptive license plate recognition system which detects and recognizes license plate at real-time by using projected plane convolution and Decision Tree Classifier is proposed. And it was tested in circumstances which presence of complex background. Generally, in expressway tollgate or gateway of parking lots, it is very difficult to detect and segment license plate because of size, entry angle and noisy problem of vehicles due to CCD camera and road environment. In the proposed algorithm, we suggested to extract license plate candidate region after going through image acquisition process with inputted real-time image, and then to compensate license size as well as gradient of vehicle with change of vehicle entry position. The proposed algorithm can exactly detect license plate using accumulated edge, projected convolution and chain code labeling method. And it also segments letter of license plate using adaptive binary method. And then, it recognizes license plate letter by applying hybrid pattern vector method. Experimental results show that the proposed algorithm can recognize the front and rear direction license plate at real-time in the presence of complex background environments. Accordingly license plate detection rate displayed $98.8\%$ and $96.5\%$ successive rate respectively. And also, from the segmented letters, it shows $97.3\%$ and $96\%$ successive recognition rate respectively.