• Smart Structures and Systems
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• v.13 no.6
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• pp.901-925
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• 2014

The reliability of a Bridge management System depends on the quality of visual inspection and the reliable estimation of bridge condition rating. However, the current practices of visual inspection have been identified with several limitations, such as: they are time-consuming, provide incomplete information, and their reliance on inspectors' experience. To overcome such limitations, this paper presents an approach of automating the prediction of condition rating for bridges based on digital image analysis. The proposed methodology encompasses image acquisition, development of 3D visualization model, image processing, and condition rating model. Under this method, scaling defect in concrete bridge components is considered as a candidate defect and the guidelines in the Ontario Structure Inspection Manual (OSIM) have been adopted for developing and testing the proposed method. The automated algorithms for scaling depth prediction and mapping of condition ratings are based on training of back propagation neural networks. The result of developed models showed better prediction capability of condition rating over the existing methods such as, Naïve Bayes Classifiers and Bagged Decision Tree.

• Journal of Internet Computing and Services
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• v.9 no.4
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• pp.133-142
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• 2008

This paper conceives and implements an activity analysis method as a tool to be used for workflow visual verification and mining. One of the recent issues in the workflow and business process literature is to refine and to improve the deployed workflows and business processes. The activity analysis method proposed in this paper provides a way to fine a set of activities being directly affected by the specific activity that a user tries to change its properties. I would strongly believe that the method can be a useful solution for the dynamic changes and visual verifications problems of workflow models as well as the workflow process mining problems. Finally, to prove the possibility of the proposed method and its applicability, we apply to a workflow model of the electronic approval system run by a real corporation.

• International Journal of Contents
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• v.11 no.3
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• pp.47-53
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• 2015

Visual object tracking is a fundamental problem in the field of computer vision, as it needs a proper model to account for drastic appearance changes that are caused by shape, textural, and illumination variations. In this paper, we propose a feature-based visual-object-tracking method with a sparse representation. Generally, most appearance-based models use the gray-scale pixel values of the input image, but this might be insufficient for a description of the target object under a variety of conditions. To obtain the proper information regarding the target object, the following combination of features has been exploited as a corresponding representation: First, the features of the target templates are extracted by using the HOG (histogram of gradient) and LBPs (local binary patterns); secondly, a feature-based sparsity is attained by solving the minimization problems, whereby the target object is represented by the selection of the minimum reconstruction error. The strengths of both features are exploited to enhance the overall performance of the tracker; furthermore, the proposed method is integrated with the particle-filter framework and achieves a promising result in terms of challenging tracking videos.

• Smart Structures and Systems
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• v.30 no.3
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• pp.287-301
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• 2022

The machine-vision based structural displacement measurement methods are widely used due to its flexible deployment and non-contact measurement characteristics. The accuracy of vision measurement is directly related to the image resolution. In the field of computer vision, super-resolution reconstruction is an emerging method to improve image resolution. Particularly, the deep-learning based image super-resolution methods have shown great potential for improving image resolution and thus the machine-vision based measurement. In this article, we firstly review the latest progress of several deep learning based super-resolution models, together with the public benchmark datasets and the performance evaluation index. Secondly, we construct a binocular visual measurement platform to measure the distances of the adjacent corners on a chessboard that is universally used as a target when measuring the structure displacement via machine-vision based approaches. And then, several typical deep learning based super resolution algorithms are employed to improve the visual measurement performance. Experimental results show that super-resolution reconstruction technology can improve the accuracy of distance measurement of adjacent corners. According to the experimental results, one can find that the measurement accuracy improvement of the super resolution algorithms is not consistent with the existing quantitative performance evaluation index. Lastly, the current challenges and future trends of super resolution algorithms for visual measurement applications are pointed out.

• Journal of The Korean Ophthalmological Society
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• v.59 no.11
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• pp.1062-1070
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• 2018

Purpose: We evaluated the prognostic factors of open globe injuries in children and adolescents, and compared the ocular trauma score (OTS) and pediatric penetrating ocular trauma score (POTS). Methods: We performed a retrospective review of 77 children under 18 years of age who visited our clinic with open globe injuries between May 1993 and April 2014. We investigated the factors that may affect final visual acuity. We also compared the OTS and POTS using receiver operating characteristic curves as a method to predict final visual acuity. Results: By univariate analysis, an initial visual acuity less than 20/200, globe rupture, wound size greater than 7.0 mm, retinal detachment, lens dislocation, and total number of operations contributed to worse visual outcomes (<20/200). Conversely, central corneal involvement, traumatic cataract, wound size less than 7.0 mm, and initial visual acuity greater than 20/200 were better prognostic indicators (${\geq}20/32$). Both OTS and POTS had diagnostic value as a predictor of final visual acuity, although there were no statistically significant differences between the two scoring systems. Conclusions: Initial visual acuity and wound size are important prognostic factors for the final visual acuity in children and adolescent, following open globe injuries. Both OTS and POTS are reliable prognostic models for open globe injuries in children and adolescents.

• Journal of Korea Multimedia Society
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• v.23 no.10
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• pp.1250-1257
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• 2020

The early detection of diseases is important in agriculture because diseases are major threats of reducing crop yield for farmers. The shape and color of plant leaf are changed differently according to the disease. So we can detect and estimate the disease by inspecting the visual feature in leaf. This study presents a vision-based leaf classification method for detecting the diseases of tomato crop. ResNet-50 model was used to extract the visual feature in leaf and classify the disease of tomato crop, since the model showed the higher accuracy than the other ResNet models with different depths. We propose a new ensemble approach using several DCNN classifiers that have the same structure but have been trained at different ranges in the DCNN layers. Experimental result achieved accuracy of 97.19% for PlantVillage dataset. It validates that the proposed method effectively classify the disease of tomato crop.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2008.04a
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• pp.596-601
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• 2008

This paper presents how to develop visual design tools for construction of strut-and-tie models(S (STM). STMs have shown internal force flows for dimensioning and proportioning of D-regions of reinforced concrete structures. In order to select an appropriate strut-and-tie model some interactive graphic tools are necessary to help designers compare alternatives by changing the geometry of initial STM. This study proposes to use force polygons representing the equilibrium state of STM. The change of STM dynamically shows change of force magnitudes by force polygon. Once the geometry of STM is determined the detailing design process is required in the next procedure.

• Journal of the Society of Naval Architects of Korea
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• v.38 no.2
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• pp.53-61
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• 2001

A cutting machine for freeform hull surfaces of ship models is developed and a servo system is employed for tool path control. The servo system consists of BLDC(Blushless DC) motor, control driver and host controller. Also PI controller is applied for precision processing. GUI(Graphic User Interface) was realized by visual c++ for the convenience of users. Free form surfaces are formed by the cutting machine developed in the Ocean Engineering Wide Tank of the University of Ulsan.

• Korean Institute of Interior Design Journal
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• no.38
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• pp.225-232
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• 2003

The purpose of this study is to select the optimal and minimum transmittance for visual amenity in office buildings. This study progressed as follows. The first, we select 5 films with various transmittance based on the current film makers whose films being used on the windows of office building nowadays and the case study of construction. And then we choose 6 kinds of transmittance as evaluation object including plain glass. The second, we made a mock-up models having different transmittance on the southern windows with model of real scale office building. The third, we select 17 pairs of adjectives for the evaluation of visual comfort on interior or exterior conditions with transmittance factor. The fourth, subjective evaluation experiment was done using selected evaluation adjectives and the result was analyzed. The results are as follows : the minimum transmittance appropriate for the office building is 30%∼40% and the optimal transmittance range is 40%∼60%.

• Journal of Fashion Business
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• v.6 no.6
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• pp.1-11
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• 2002

The attractiveness of the textile fabrics are generally judged by visual or tactile evaluation methods. Since the surface of the textile materials are so diverse that the visual factors such as optical properties or luster of the fabrics are not easily measurable. While most of the cotton fabrics are not so much lustrous, calendering process could impart the cotton fabric better luster. Also, the general grade silk-like polyester fabrics resemble silk fabric with some limit in terms of luster properties. One of the interesting fabrics showing subdued luster is the velvet fabrics with dark shade. In this study, the luster related properties are examined using some image analysis methods. Yarn models based on the fabric weave types were developed to further investigate the effect of fabric crimp shapes due to weave on the optical properties or luster of the fabrics.