• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.8
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• pp.3488-3500
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• 2020

At the present time, the economy continues to flourish, and private cars have become the means of choice for most people. Therefore, the license plate recognition technology has become an indispensable part of intelligent transportation, with research and application value. In recent years, the convolution neural network for image classification is an application of deep learning on image processing. This paper proposes a strategy to improve the YOLO model by studying the deep learning convolutional neural network (CNN) and related target detection methods, and combines the OpenCV and TensorFlow frameworks to achieve efficient recognition of license plate characters. The experimental results show that target detection method based on YOLO is beneficial to shorten the training process and achieve a good level of accuracy.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.2
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• pp.96-101
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• 2011

Vanishing point can be defined as a point generated by converged perspective lines, which are parallel in the real world. In this paper, we propose a real-time vanishing point detection algorithm using this fundamental feature of vanishing point. The existing methods 1) require high computational cost or 2) are restricted to specific image contents. The proposed method detects the vanishing point in images based on the block-wise HOG (Histogram of Oriented Gradient) descriptor. First, we compute the HOG descriptor in a block-wise manner, then estimate the location of the vanishing point using the proposed dynamic programing. Experiments are performed on diverse images to confirm the efficiency of the proposed method.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.23 no.3
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• pp.282-290
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• 2013

A new method is presented that uses guided wave techniques for sludge and blockages detection in long-range pipelines. Existing techniques have the limitations that the sludge position needs to be known a priori and the area to be inspected needs to be accessible. Two guided wave techniques have been developed which allow the sludge or blockages to be detected remotely without the need to access the specific location where the pipe is blocked, nor to open the pipe. The first technique measures the reflection of guided waves by sludge which can be used to accurately locate the blocked region; the second technique detects sludge by revealing the changes to the transmitted guided waves propagating in the blocked region or after it. The two techniques complement each other and their combination leads to a reliable sludge or blockage detection. Various types of realistic sludge have been considered in the study and the practical capabilities of the two techniques have been demonstrated.

• Smart Structures and Systems
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• v.19 no.4
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• pp.393-402
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• 2017

Many vibration-based global damage detection methods attempt to extract modal parameters from vibration signals as the main structural features to detect damage. The local flexibility method is one promising method that requires only the first few fundamental modes to detect not only the location but also the extent of damage. Generally, the mode shapes in the lateral degree of freedom are extracted from lateral vibration signals and then used to detect damage for a beam structure. In this study, a new approach which employs the mode shapes in the rotary degree of freedom obtained from the macro-strain vibration signals to detect damage of a beam structure is proposed. In order to facilitate the application of mode shapes in the rotary degree of freedom for beam structures, the local flexibility method is modified and utilized. The proposed rotary approach is verified by numerical and experimental studies of simply supported beams. The results illustrate potential feasibility of the proposed new idea. Compared to the method that uses lateral measurements, the proposed rotary approach seems more robust to noise in the numerical cases considered. The sensor configuration could also be more flexible and customized for a beam structure. Primarily, the proposed approach seems more sensitive to damage when the damage is close to the supports of simply supported beams.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.317-321
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• 2008

Piping in the Nuclear Power plants (NPP) are mostly consisted of carbon steel pipe. The wall thinning defect is mainly occurred by the affect of the flow accelerated corrosion (FAC) of fluid which flows in carbon steel pipes. This type of defect becomes the cause of damage or destruction of piping. Therefore, it is very important to measure defect which is existed not only on the welding partbut also on the whole field of pipe. Over the years, Infrared thermography (IRT) has been used as a non destructive testing methods of the various kinds of materials. This technique has many merits and applied to the industrial field but has limitation to the materials. Therefore, this method was combined with lock-in technique. So IRT detection resolution has been progressively improved using lock-in technique. In this paper, the quantitative analysis results of the location and the size of wall thinning defect that is artificially processed inside the carbon steel pipe by using IRT are obtained.

• Journal of the Korea Computer Industry Society
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• v.3 no.7
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• pp.901-914
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• 2002

In this paper, We propose an efficient automatic caption detection and location method, caption recognition using FE-MCBP(Feature Extraction based Multichained BackPropagation) neural network for content based retrieval of video. Frames are selected at fixed time interval from video and key frames are selected by gray scale histogram method. for each key frames, segmentation is performed and caption lines are detected using line scan method. lastly each characters are separated. This research improves speed and efficiency by color segmentation using local maximum analysis method before line scanning. Caption detection is a first stage of multimedia database organization and detected captions are used as input of text recognition system. Recognized captions can be searched by content based retrieval method.

• Journal of Auto-vehicle Safety Association
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• v.9 no.3
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• pp.24-30
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• 2017

This paper presents the development of laser scanner based static obstacle detection algorithm for vehicle localization on lane lost section. On urban autonomous driving, vehicle localization is based on lane information, GPS and digital map is required to ensure. However, in actual urban roads, the lane data may not come in due to traffic jams, intersections, weather conditions, faint lanes and so on. For lane lost section, lane based localization is limited or impossible. The proposed algorithm is designed to determine the lane existence by using reliability of front vision data and can be utilized on lane lost section. For the localization, the laser scanner is used to distinguish the static object through estimation and fusion process based on the speed information on radar data. Then, the laser scanner data are clustered to determine if the object is a static obstacle such as a fence, pole, curb and traffic light. The road boundary is extracted and localization is performed to determine the location of the ego vehicle by comparing with digital map by detection algorithm. It is shown that the localization using the proposed algorithm can contribute effectively to safe autonomous driving.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.9 no.1
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• pp.47-54
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• 1991

In this study, the accuracy of three dimensional location was improved by self calibration bundle method with additional parameter, which is to correct systematic error through detection and elimination of the gross error from updated reference variance for observation values in photogram-metry. In this study, with the result of comparing accuracy of each method, correcting systematic error is more effective after gross error detection and when observation values are contained more than two gross error the point with maximum correlation value is detected by masking effect of least square adjustment.

• Journal of Gastric Cancer
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• v.14 no.1
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• pp.1-6
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• 2014

Aerobic glycolysis has been the most important hypothesis in cancer metabolism. It seems to be related to increased bioenergetic and biosynthetic needs in rapidly proliferating cancer cells. To this end, F-18 fluorodeoxyglucose (FDG), a glucose analog, became widely popular for the detection of malignancies combined with positron emission tomography/computed tomography (PET/CT). Although the potential roles of FDG PET/CT in primary tumor detection are not fully established, it seems to have a limited sensitivity in detecting early gastric cancer and mainly signet ring or non-solid types of advanced gastric cancer. In evaluating lymph node metastases, the location of lymph nodes and the degree of FDG uptake in primary tumors appear to be important factors affecting the diagnostic accuracy of PET/CT. In spite of the limited sensitivity, the high specificity of PET/CT for lymph node metastases may play an important role in changing the extent of lymphadenectomy or reducing futile laparotomies. For peritoneal metastases, PET/CT seems to have a poorer sensitivity but a better specificity than CT. The roles of PET/CT in the evaluation of other distant metastases are yet to be known. Studies including primary tumors with low FDG uptake or peritoneal recurrence seem suffer from poorer diagnostic performance for the detection of recurrent gastric cancer. There are only a few reports using FDG PET/CT to predict response to neoadjuvant or adjuvant chemotherapy. A complete metabolic response seems to be predictive of more favorable prognosis.

• Structural Engineering and Mechanics
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• v.38 no.6
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• pp.715-732
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• 2011

A novel structural damage detection method with a new damage index has been recently proposed by the authors based on the statistical moments of dynamic responses of shear building structures subject to white noise ground motion. The statistical moment-based damage detection (SMBDD) method is theoretically extended in this paper with general application. The generalized SMBDD method is more versatile and can identify damage locations and damage severities of many types of building structures under various external excitations. In particular, the incomplete measurements can be considered by the proposed method without mode shape expansion or model reduction. Various damage scenarios of two general forms of building structures with incomplete measurements are investigated in consideration of different excitations. The effects of measurement noise are also investigated. The damage locations and damage severities are correctly identified even when a high noise level of 15% and incomplete measurements are considered. The effectiveness and versatility of the generalized SMBDD method are demonstrated.