• Journal of KIISE
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• v.42 no.5
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• pp.642-651
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• 2015

A vanishing point is a point where parallel lines converge, and they become evident when a camera's lenses are used to project 3D space onto a 2D image plane. Vanishing point detection is the use of the information contained within an image to detect the vanishing point, and can be utilized to infer the relative distance between certain points in the image or for understanding the geometry of a 3D scene. Since parallel lines generally exist for the artificial structures within images, line-detection-based vanishing point-detection techniques aim to find the point where the parallel lines of artificial structures converge. To detect parallel lines in an image, we detect edge pixels through edge detection and then find the lines by using the Hough transform. However, the various textures and noise in an image can hamper the line-detection process so that not all of the lines converging toward the vanishing point are obvious. To overcome this difficulty, it is necessary to assign a different weight to each line according to the degree of possibility that the line passes through the vanishing point. While previous research studies assigned equal weight or adopted a simple weighting calculation, in this paper, we are proposing a new method of assigning weights to lines after noticing that the lines that pass through vanishing points typically belong to artificial structures. Experimental results show that our proposed method reduces the vanishing point-estimation error rate by 65% when compared to existing methods.

• Journal of the Korea institute for structural maintenance and inspection
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• v.28 no.3
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• pp.66-73
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• 2024

Stay-cable is one of the most important load carrying members in cable-stayed bridges. Monitoring structural integrity of stay-cables is crucial for evaluating the structural condition of the cable-stayed bridge. For stay-cables, tension and damping ratio are estimated based on modal properties as a measure of structural integrity. Since the monitoring system continuously measures the vibration for the long-term period, data acquisition systems should be stable and power-efficiency as the hardware system. In addition, massive signals from the data acquisition systems are continuously generated, so that automated analysis system should be indispensable. In order to fulfill these purpose simultaneously, this study presents an autonomous cable monitoring system based on domain-knowledge using IoT for continuous cable monitoring systems of cable-stayed bridges. An IoT system was developed to provide effective and power-efficient data acquisition and on-board processing capability for Edge-computing. Automated peak-picking algorithm using domain knowledge was embedded to the IoT system in order to analyze massive data from continuous monitoring automatically and reliably. To evaluate its operational performance in real fields, the developed autonomous monitoring system has been installed on a cable-stayed bridge in Korea. The operational performance are confirmed and validated by comparing with the existing system in terms of data transmission rates, accuracy and efficiency of tension estimation.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.1
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• pp.103-119
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• 2010

In this paper, we propose a subpixel shift estimation method using phase correlation with a local region for the registration of noisy images. Phase correlation is commonly used to estimate the subpixel shift between images, which is derived from analyzing shifted and downsampled images. However, when the images are affected by additive white Gaussian noise and aliasing artifacts, the estimation error is increased. Thus, instead of using the whole image, the proposed method uses a specific local region that is less affect by noises. In addition, to improve the estimation accuracy, iterative phase correlation is applied between selected local regions rather than using a fitting function. the restricted range is determined by analyzing the maximum peak and the two adjacent values of the inverse Fourier transform of the normalized cross power spectrum. In the experiments, the proposed method shows higher accuracy in registering noisy images than the other methods. Thus, the edge-sharpness and clearness in the super-resolved image is also improved.

• Journal of the Korea Society of Computer and Information
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• v.18 no.9
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• pp.53-62
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• 2013

This paper proposes a method of automatically predicting the vanishing point for the purpose of detecting the road region from natural images. The proposed method stably detects the vanishing point in the road environment by analyzing the dominant orientation of the image and predicting the vanishing point to be at the position where the feature components of the image are concentrated. For this purpose, in the first stage, the image is partitioned into sub-blocks, an edge sample is selected randomly from within the sub-block, and RANSAC is applied for line fitting in order to analyze the dominant orientation of each sub-block. Once the dominant orientation has been detected for all blocks, we proceed to the second stage and randomly select line samples and apply RANSAC to perform the fitting of the intersection point, then measure the cost of the intersection model arising from each line and we predict the vanishing point to be located at the average point, based on the intersection point model with the highest cost. Lastly, quantitative and qualitative analyses are performed to verify the performance in various situations and prove the efficiency of the proposed algorithm for detecting the vanishing point.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.3
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• pp.433-438
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• 2017

Containing an Angle-of-Arrival(: AOA) estimation and interference suppression techniques, an adaptive beamformer is one of core techniques for the Signal Intelligence(: SIGINT) which collect various intelligence utilizing cutting edge devices including the radar and satellite. It generates a beam with the directivity in a corresponding direction, to efficiently receive a signal from the specific direction, using antenna array. In this paper, we present the received signal model including interference signals and noise, which can be applied to an input of the signal intelligence satellite system equipped with the AOA estimation and the interference cancellation techniques, and analysis the characteristics of various signals, which can be included in the proposed received signal model. This proposed signal model can be directly applied to the performance evaluation for a variety of beamforming techniques. Also, we verify the spectrum characteristic of the presented received signal model in the frequency domain through computer simulation examples.

• Journal of the Korea Institute of Military Science and Technology
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• v.20 no.1
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• pp.40-47
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• 2017

To classify the vehicle targets automatically using thermal images, there are usually two main categories of feature extraction method, local and shape feature extraction methods. Since thermal images have less texture information than color images, the shape feature extraction method is useful when the segmentation results are correct. However, if there are some errors in target segmentation, the shape feature may contain some errors, then the classification accuracy can be decreased. To overcome these problems, in this paper, we propose the segmentation reliability estimation method for target classification. The segmentation reliability can be estimated by using the difference information of average intensities and edge energies between the target and the background area. The estimated segmentation reliability is applied in the decision level fusion method of classification results using both shape and local features. Experiment results using the thermal images of the vehicle targets (main battle tank, armored personnel carrier, military truck, and an estate car) show that the proposed classification method and the segmentation reliability estimation method have a good performance in classification accuracy.

• Transactions of the Korean Society of Automotive Engineers
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• v.7 no.6
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• pp.214-221
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• 1999

Spot welding is very important and useful technology in fabriaction of the thin sheet structure such as the automobile, train and air craft, Because fatigue strength of the spot welding point is however considerably lower than base metal due to stress concentration at the nugget edge, reasonable fatigue strength evaluation of spot welded lap joint is very important to estimate the reliability and durability of th spot welded structure and to establish a criterion of ling life fatigue design. For reasonalbe fatigue strength evaluation, it is necessary to estimate the fatigue strength of spot welded lap joints, systematically. So far, many investigators have numerically and experimentally studied on the systematic fatigue strength estimation for various spot welded lap joints, and the methods suggested has been considerably accumulated. By the way, for applying them in practical fatigue design of the thin sheet structure fabricated by spot welding ,it is also necessary to verify their efficiency and reliability on the predicted results, Therefore, in this study, a statistical fatigue strength estimation method for spot welded lap joints was developed by using the Weibull probability distribution function. From the result, it was found that fatigue strength and fatigue life of the spot welded lap joints having various dimension were able to be statically predicted . And also, a reliable criterion for long life fatigue design of the spot welded lap joint could be established.

• Journal of Broadcast Engineering
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• v.10 no.4 s.29
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• pp.576-586
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• 2005

This paper presents a new estimation and representation of a disparity map for stereo-based video communication systems. Several pixel-based and block-based algorithms have been proposed to estimate the disparity map. While the pixel-based algorithms can achieve high accuracy in computing the disparity map, they require a lost of bits to represent the disparity information. The bit rate can be reduced by the block-based algorithm, sacrificing the representation accuracy. In this paper, the block enclosing a distinct edge is divided into two regions and the disparity of each region is set to that of a neighboring block. The proposed algorithm employs accumulated histograms and a neural network to classify a type of a block. In this paper, we proved that the proposed algorithm is more effective than the conventional algorithms in estimating and representing disparity maps through several experiments.

• Proceedings of the KOSOMBE Conference
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• v.1997 no.05
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• pp.123-126
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• 1997

We present a method for the estimation of 3D solid angle assessment of the acetabular coverage of the femoral head in 3D space. At first, femoral head and acetabulum is segmented from the original CT scan images. The slice thickness is 1.5mm and the number of slices is usually 30-40 to cover the entire acetabulum. The superior half of the femoral head is modeled as part of a sphere. Thus, the axial cross sections of the upper half of the femoral head are also modeled as circles. A set of points from each outline image of femoral head is fitted recursively into a circle by minimizing root-mean-square (RMS) error. With these fitted circles, a center point of the femoral head model is evaluated. This is a reference point for calculating the solid angle of the acetabular inner surface. Next, the tangent lines connecting from a set of points of the acetabular edge to the center of the fitted sphere are obtained. The lines pass through the unit sphere whose center is the same as that of the femoral head. With the points on the unit sphere, we calculate area and estimate the solid angle. Based on this solid angle, the deformity of the acetabulum is analyzed. In case of normal subject, the solid angle is about 4.3 (rad) and acetabular coverage is 68%.

• The KIPS Transactions:PartB
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• v.12B no.1 s.97
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• pp.17-24
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• 2005

In this paper, we will show that a control search methodology is a alternative method of a sequential search which is difficult in finding books for arrangement at library or a bookstore when books are out of place. To solve the problem of the sequential search, we apply a edge operator and the Hough Transform to boundary of a taken photograph image book. We generate histogram by a projected image from boundary range of selected books and select title areas from this and possible areas which are a character number of title, authors, a publishing company and an array sequence. Finally, we can select the final possible area of a book location by a curve fitting and a regression line extraction, and show utility through experiment.