• Smart Structures and Systems
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• 제29권1호
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• pp.207-220
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• 2022

Structural health monitoring (SHM) plays a vital role in the maintenance and operation of constructions. In recent years, autonomous inspection has received considerable attention because conventional monitoring methods are inefficient and expensive to some extent. To develop autonomous inspection, a potential approach of crack identification is needed to locate defects. Therefore, this study exploits two deep learning-based segmentation models, DeepLabv3+ and Mask R-CNN, for crack segmentation because these two segmentation models can outperform other similar models on public datasets. Additionally, impacts of label quality on model performance are explored to obtain an empirical guideline on the preparation of image datasets. The influence of image cropping and label refining are also investigated, and different strategies are applied to the dataset, resulting in six alternated datasets. By conducting experiments with these datasets, the highest mean Intersection-over-Union (mIoU), 75%, is achieved by Mask R-CNN. The rise in the percentage of annotations by image cropping improves model performance while the label refining has opposite effects on the two models. As the label refining results in fewer error annotations of cracks, this modification enhances the performance of DeepLabv3+. Instead, the performance of Mask R-CNN decreases because fragmented annotations may mistake an instance as multiple instances. To sum up, both DeepLabv3+ and Mask R-CNN are capable of crack identification, and an empirical guideline on the data preparation is presented to strengthen identification successfulness via image cropping and label refining.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1989년도 한국자동제어학술회의논문집; Seoul, Korea; 27-28 Oct. 1989
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• pp.1005-1010
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• 1989

A refined version of automatic micro-organism recognition and identification method, 'O.I.S.M.2' is proposed in this paper, using image processing based on an expert system. This proposed method is based on the segmentation of the organism image, characterizing segment features, which are independent of individual size and length. Complicated shapes of organisms are divided into basic shape segments defined in this paper such as lines, circles, ovals etc. Organisms can then be expressed simply in a set of segments, regardless their individual differences.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2001년도 하계종합학술대회 논문집(2)
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• pp.75-78
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• 2001

In this paper, we proposed a personal identification method using binay image encryption technique and decryption system in JTC structure. Logo which represents the group symbol was encrypted with personal fingerprint and JTC structure decrypts this logo. The logo can not decrypted by other unused fingerprint even if the encrypted image was lost or stolen. So this method can give more safe personal identification.

• International journal of advanced smart convergence
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• 제4권2호
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• pp.84-93
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• 2015

This study is for the development of Cover Glass Grinding Processing System. This system is developed for manufacturing a mass product system grinding cover glasses with highly precise mechanism, and we improved resulted quality. In the development process, we developed a complete process technology through mechanical design, image processing technology, spindle control, mark identification algorithm etc. With this cover glass grinding development, we could developed process technology, image processing technology, organization mechanisms and control algorithms.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권12호
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• pp.5087-5102
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• 2015

Rapid popularization of smart cell phone equipped with camera has led to a number of new legal and criminal problems related to multimedia such as digital image, which makes cell phone source identification an important branch of digital image forensics. This paper proposes a classifier combination based source identification strategy for cell phone images. To identify the outlier cell phone models of the training sets in multi-class classifier, a one-class classifier is orderly used in the framework. Feature vectors including color filter array (CFA) interpolation coefficients estimation and multi-feature fusion is employed to verify the effectiveness of the classifier combination strategy. Experimental results demonstrate that for different feature sets, our method presents high accuracy of source identification both for the cell phone in the training sets and the outliers.

• 한국융합학회논문지
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• 제9권2호
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• pp.295-302
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• 2018

본 연구는 국내 프로야구단의 CSR활동에 대한 팬들의 지각이 구단평판, 구단동일시 및 모기업이미지와 어떠한 관계를 형성하고 있는지를 실증적으로 규명하는데 목적이 있다. 이를 위해 수도권지역 프로야구단인 LG트윈스, 두산 베어스, SK 와이번스 및 KT 위즈의 홈팀 팬 277명을 대상으로 설문조사를 실시하여 다음과 같은 결과를 얻었다. 첫째, 프로야구단의 CSR활동은 구단평판에 긍정적인 영향을 미치고 있는 것으로 나타났다. 둘째, 프로야구단의 CSR활동은 구단동일시에 긍정적인 영향을 미치고 있는 것으로 나타났다. 셋째, 구단평판은 프로야구단 모기업이미지에 긍정적인 영향을 미치고 있는 것으로 나타났다. 넷째, 구단동일시는 프로야구단 모기업이미지에 긍정적인 영향을 미치고 있는 것으로 나타났다.

• 디지털융복합연구
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• 제17권9호
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• pp.105-114
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• 2019

융복합시대 통신기업이 디지털격차를 해소하려는 공유가치창출활동(CSV)에 대해 본 연구는 CSV가 브랜드 이미지, 소비자행동의도에 미치는 인과관계를 CSV의도성과 기업-소비자 동일시라는 심리적 변수를 통해서 구조방정식 모형으로 확인해 보고자 하였다. 이를 위해 KT CSV활동에 참여하고 있는 시니어를 대상으로 설문조사를 실시하여 얻은 198부의 설문지를 Smart PLS 2.0을 사용하여 분석하였다. 분석결과 CSV는 CSV의도성에 부(-)의 영향을 미치고, CSV의도성은 브랜드 이미지에 부(-)의 영향을 미친다는 두 가지 가설은 기각되었다. 반면 CSV는 기업-소비자동일시에 긍정적인 영향을 미치고, 기업-소비자 동일시는 브랜드 이미지와 구매의도, 지불의사에 긍정적 영향을 미치는 것으로 확인되었다. 이로써 통신기업의 CSV가 소비자행동의도에 미치는 인과관계를 실증하였고, CSV실행전략을 수립하려는 기업들에게 CSV성과를 높이기 위한 소비자 참여와 커뮤니케이션 강화의 필요성을 제시하였다. 향후에는 융복합 솔루션을 적용한 CSV연구에 기업이미지와 브랜드 이미지 비교 연구로 확대할 필요가 있겠다.

• 반도체디스플레이기술학회지
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• 제18권3호
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• pp.31-35
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• 2019

Human beings have been fascinated by the applicability of the medium of photography since the device was first introduced in the thirteenth century to acquire images by attempting primitive and rudimentary approaches. In the 21st century, it has been developed as a wide range of technology that enables not only the application of artistic expression as a method of replacing the human-hand-painted screen but also the planar recording form in the format of video or image. It is more effective to use the information extracted from the image data rather than to use a randomly given file name in order to provide a variety of services in the offline or online system. When extracting an identifier from a region of an image, high cost cannot be avoided. This paper discusses the image entropy-based approach and proposes a linear methodology to measure the image entropy in an effort to devise a solution to this method.

• Journal of the Optical Society of Korea
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• 제4권1호
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• pp.19-22
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• 2000

A new image encoding and identification scheme is proposed for security verification by us-ing a CGH(computer generated hologram), random phase mask, and a correlation technique. The encrypted image, which is attached to the security product, is made by multiplying a QP- CGH(quadratic phase CGI) with a random phase function. The random phase function plays a key role when the encrypted image is decrypted. The encrypted image can be optically recovered by a 2-f imaging system and automatically verified for personal identification by a 4-f correlation system. Simulation results show the proposed method can be used for both the reconstruction of an original image and the recognition of an encrypted image.

• 반도체디스플레이기술학회지
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• 제16권1호
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• pp.6-10
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• 2017

Recent enhancement in the still image acquisition devices has been widely perpetrated into the daily life of the common people. Due to this trend, the voluminous still images, that are produced and shared in the personal or the massive storage, need to controlled with effective and efficient management. The human-devised or system-generated still image identifiers used for the identification of the images are at risk in the situation of unexpected changing or eliminating of the identifiers. In this paper, we propose a parallel processing based method for still image identifier generation by utilizing the still image internal features.