• Smart Structures and Systems
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• v.23 no.4
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• pp.359-371
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• 2019

As part of a structural health monitoring system, the relative geometric relationship between a ship and bridge has been recognized as important for bridge authorities and ship owners to avoid ship-bridge collision. This study proposes a novel computer vision method for the real-time geometric parameter identification of moving ships based on a single shot multibox detector (SSD) by using transfer learning techniques and monocular vision. The identification framework consists of ship detection (coarse scale) and geometric parameter calculation (fine scale) modules. For the ship detection, the SSD, which is a deep learning algorithm, was employed and fine-tuned by ship image samples downloaded from the Internet to obtain the rectangle regions of interest in the coarse scale. Subsequently, for the geometric parameter calculation, an accurate ship contour is created using morphological operations within the saturation channel in hue, saturation, and value color space. Furthermore, a local coordinate system was constructed using projective geometry transformation to calculate the geometric parameters of ships, such as width, length, height, localization, and velocity. The application of the proposed method to in situ video images, obtained from cameras set on the girder of the Wuhan Yangtze River Bridge above the shipping channel, confirmed the efficiency, accuracy, and effectiveness of the proposed method.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.3 s.309
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• pp.84-91
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• 2006

In this paper, we present a new segmentation algorithm for color images based on mathematical morphology and a Gaussian mixture model(GMM). We use the morphological operations to determine the number of components in a mixture model and to detect their modes of each mixture component. Next, we have adopted the GMM to represent the probability distribution of color feature vectors and used the deterministic annealing expectation maximization (DAEM) algorithm to estimate the parameters of the GMM that represents the multi-colored objects statistically. Finally, we segment the color image by using posterior probability of each pixel computed from the GMM. The experimental results show that the morphological operation is efficient to determine a number of components and initial modes of each component in the mixture model. And also it shows that the proposed DAEM provides a global optimal solution for the parameter estimation in the mixture model and the natural color images are segmented efficiently by using the GMM with parameters estimated by morphological operations and the DAEM algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.5
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• pp.438-443
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• 2008

In this paper, segmenting and classifying low contrast defects on flat panel display is one of the key problems for automatic inspection system in practice. Problems become more complicated when the quality of acquired image is degraded by the illumination irregularity. Many algorithms are developed and implemented successfully for the defects segmentation. However, vision algorithms are inherently prone to be dependent on parameters to be set manually. In this paper, one morphological segmentation algorithm is chosen and a technique using frequency domain analysis of input images is developed for automatically selection the morphological parameter. An extensive statistical performance analysis is performed to compare the developed algorithms.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.7
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• pp.116-126
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• 1996

In this paper, we propose a new termination rule for the iterative restoration of degraded images, by which the number of iterations can be dramatically reduced. This rule uses a parameter, called noise suppression factor (NSF), to appropriately teminate the iteration process, reduces a lot the computational load, and avoids the amplification of noise for the better quality. We also propose a method using the morphological filters, when applied to the resulting image, that will significantly reduce the ringing effect which would otherwise exist in the boundary of the image. Simulation with the blurred lena image with gaussian noise showns that the proposed termination rule combined with the morphological filtering gives the restored image with much improved quality.

• Proceedings of the KOSOMBE Conference
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• v.1996 no.05
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• pp.103-107
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• 1996

In this paper, We propose an algorithm for reconstitution of chromosome images to extract its morphological feature parameters. It is reconstituted from 460 chromosome images using the 32 direction line algorithm. We extract three morphological feature parameters such as centromeric index, relative length ratio, and relative area ratio. The experiment results show that our method is batter than that of other researchers comparing with the error of feature parameters.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 2001.06a
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• pp.30-35
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• 2001

The morphological analysis of wear particle is a very effective means for machine condition monitoring and fault diagnosis. In order to describe morphology of various wear particle, the wear test was carried oui under friction experimental conditions. And fractal descriptors was applied to boundary and surface of wear particle with image processing system. These descriptors to analyze shape and surface wear particle are share fractal dimension and surface fractal dimension. The boundry fractal dimension can be derived from the boundary profile and surface fractal dimension can be determined b)r sum of intensity difference of surface pixel. The morphology of wear particles can be effectively obtained by two fractal dimensions.

• Proceedings of the Korean Institute of Surface Engineering Conference
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• 2003.05a
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• pp.4-4
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• 2003

Various Cu films were fabricated using sputtering and electroplating with and without additive, and their surface damages after annealing were investigated. After annealing at 43SoC, the difference between damage morphologies of the films was observed. In some films stress-induced grooves along the grain boundaries were observed, while in the others voids at the grain boundary triple junctions were observed. It was also observed that the stress-induced groove was formed along the high energy grain boundaries. It was found out that the difference of the morphologies of surface damages in Cu films depends on not process type but grain boundary characteristics. To explain the morphological difference of surface damages, a simple parameter considering the contributions of grain structures and grain boundary characteristics to surface and grain boundary diffusions is suggested. The effective grain boundary area, which is a function of grain size, film thickness and the fraction of high energy grain boundaries, played a key role in the morphological difference.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.7 no.4
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• pp.42-49
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• 1998

This wear debris can be harvested from the lubricants of operating machinery and its morphology is directly related to the damage to the interacting surface from which the particles originated. The morphological identification of wear debris can therefore provide very early detection of a fault and can also often facilitate a diagnosis. The purpose of this study is to attempt the developement of intelligent system for moving condition diagnosis of the machine driving system. The four shape parameter(50% volumetric diameter, aspect, roundness and reflectivity) of war debris are used as inputs to the neural network and learned the moving condition of five values(material3, applied load 1, sliding distance 1). It is shown that identification results depend on the ranges of these shape parameter learned. The three kinds of the wear debris had a different pattern characteristics and recognized the moving condition and materials very well by neural network.

• Journal of Industrial Technology
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• v.20 no.B
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• pp.3-8
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• 2000

Low cycle fatigue life of spheroidal graphite cast iron is determined by the morphological parameters of internal graphite. The aim of this study is to clarify the effect of the number of nodular grain of spheroidal graphite cast iron on low cycle fatigue life. Two specimens that have identical average nodular grain size by changing nodular grain volume fraction and different number of nodular grain count was tested. In this paper, the parameter governing fatigue life through fatigue test, the number of nodular grain seriously affect fatigue life and nodular grain size is no longer governing parameter of it.

• The Korean Journal of Mycology
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• v.37 no.1
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• pp.55-59
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• 2009

The mushroom takes in charge of decomposer in ecosystem and its production is important indicator for sounded ecosystem function. To determine standing crop of basidiocarps(fruit body of mushroom), a weight must be measured by harvesting mushroom individual in the field. But this method has profound affection on the basidiocarps population or its surrounding condition due to habitat destruction. Thus, in this study, without harvesting any mushroom in the field, we developed allometric equation using some morphological parameters to estimate standing crop biomass of basidiocarps. Lentinula edodes, Pleurotus ostreatus, Flammulina velutipes and Conocybe tenera were used for allometry. Morphological variables of the mushroom were pileus diameter, pileus area, stipe length and stipe thickness. Consequently, all the experimental mushrooms species showed significantly correlation in biomass estimation of basidiocarps from allometric equation (p<0.05). As a result of this research, the standing biomass of the basidiocarps could be indirectly estimated with proportional expression, allometric equation drived from morphological characters.