• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.435-440
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• 2009

The scalable vector graphics (SVG) standard has allowed the complex bitmap images to be represented by vector based graphics and provided some advantages over the raster based graphics in applications, for example, where scalability is required. This paper presents an algorithmto convert bitmap images into SVG format. The algorithm is an integration of pixel-level triangulation, data dependent triangulation, a new image mesh simplification algorithm, and a polygonization process. Both triangulation techniques enable the image quality (especially the edge features) to be preserved well in the reconstructed image and the simplification and polygonization procedures reduce the size of the SVG file. Experiments confirm the effectiveness of the proposed algorithm.

• Journal of the Korean Society for Nondestructive Testing
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• v.31 no.6
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• pp.665-670
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• 2011

In this paper, a new approach to detect surface cracks from a noisy thermal image in the infrared thermography is presented using an holomorphic characteristic of temperature field in a thin plate under steady-state thermal condition. The holomorphic function for 2-D heat flow field in the plate was derived from Cauchy Riemann conditions to define a contour integral that varies according to the existence and strength of a singularity in the domain of integration. The contour integral at each point of thermal image eliminated the temperature variation due to heat conduction and suppressed the noise, so that its image emphasized and highlighted the singularity such as crack. This feature of holomorphic function was also investigated numerically using a simple thermal field in the thin plate satisfying the Laplace equation. The simulation results showed that the integral image selected and detected the crack embedded artificially in the plate very well in a noisy environment.

• 한국정보디스플레이학회:학술대회논문집
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• 2009.10a
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• pp.1022-1024
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• 2009

Stereoscopic Images provide depth information with the relative distances between the objects in the images. There are many different ways to extract disparity maps from the visible spectral images. For the infrared spectral range, the same approach cannot be utilized for the innate low resolution and colorless features because typical methods require corresponding features between the images. The authors suggest a new approach that makes use of image segmentation to obtain depth information for stereoscopic millimeter-wave images. For image segmentation a selective visual attention model based on the theory of a feature-integration of attention is used. Experimental results show the proposed method provides reasonable depth information for object shape recognition and display.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.12 no.2
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• pp.176-188
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• 1987

This paper presents a method for Digital Image Motion Restoration by inverse filtering. In order to onstruct optimal Restoration filter, We exactly have to model the degradation process, and therefrom, derive the inverse filter which has inverse charateristics of the degradation model. An Image taken from object which moves fast, is o suffer blurring. it can be modeled by integration process mathematically and analyzed to convolve a rectangular window over an image. in this paper, We analyzed it in the frequency domain, and studied a method for motion restoration using inverse filter has a directional Sinc property.

• Information Display
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• v.15 no.5
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• pp.22-32
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• 2014

The current research intends to quantify the surround luminance effects on the shape of spatial luminance CSF and to propose an image quality evaluation method that is adaptive to both surround luminance and spatial frequency of a given stimulus. The proposed image quality method extends to a model called SQRI[8]. The non-linear behaviour of the HVS was taken into account by using CSF. This model can be defined as the square root integration of multiplication between display MTF and CSF. It is assumed that image quality can be determined by considering the MTF of the imaging system and the CSF of human observers. The CSF term in the original SQRI model was replaced by the surround adaptive CSF quantified in this study and it is divided by the Fourier transform of a given stimulus. A few limitations of the current work should be addressed and revised in the future study. First, more accurate model predictions can be achievable when the actual display MTF is measured and used instead of the approximation. Then, a further improvement to the model prediction accuracy can be made when chromatic adaptation of the HVS is taken into account[45-46].

• Journal of Sensor Science and Technology
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• v.28 no.3
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• pp.152-156
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• 2019

An ultraviolet (UV) image sensor is an extremely important optoelectronic device used in scientific and medical applications because it can detect images that cannot be obtained using visible or infrared image sensors. Because photodetectors and transistors are based on different materials, conventional UV imaging devices, which have a hybrid-type structure, require additional complex processes such as a backside etching of a GaN epi-wafer and a wafer-to-wafer bonding for the fabrication of the image sensors. In this study, we developed a monolithic GaN UV passive pixel sensor (PPS) by integrating a GaN-based Schottky-barrier type transistor and a GaN UV photodetector on a wafer. Both individual devices show good electrical and photoresponse characteristics, and the fabricated UV PPS was successfully operated under UV irradiation conditions with a high on/off extinction ratio of as high as $10^3$. This integration technique of a single pixel sensor will be a breakthrough for the development of GaN-based optoelectronic integrated circuits.

• International conference on construction engineering and project management
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• 2005.10a
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• pp.503-508
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• 2005

In the modern, distributed and dynamic construction environment it is important to exchange information from different sources and in different data formats in order to improve the processes supported by these systems. Previous research has demonstrated that (i) a significant percentage of construction data is stored in semi-structured or unstructured data formats (ii) locating and identifying such data that are needed for the important decision making processes is a very hard and time-consuming task. In this paper, an automated methodology for the classification and retrieval of construction images in AEC/FM model based systems will be presented. Specifically, a combination of techniques from the areas of image processing, computer vision, and content-based image retrieval have been deployed to develop a method that can retrieve related construction site image data from components of a project model.

• Smart Media Journal
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• v.12 no.9
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• pp.45-59
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• 2023

Weakly supervised object localization (WSOL) is a task of localizing an object in an image using only image-level labels. Previous studies have followed the conventional class activation mapping (CAM) pipeline. However, we reveal the current CAM approach suffers from problems which cause original CAM could not capture the complete defects features. This work utilizes a convolutional neural network (CNN) pretrained on image-level labels to generate class activation maps in a multi-scale manner to highlight discriminative regions. Additionally, a vision transformer (ViT) pretrained was treated to produce multi-head attention maps as an auxiliary detector. By integrating the CNN-based CAMs and attention maps, our approach localizes defective regions without requiring bounding box or pixel-level supervision during training. We evaluate our approach on a dataset of apple images with only image-level labels of defect categories. Experiments demonstrate our proposed method aligns with several Object Detection models performance, hold a promise for improving localization.

• Journal of the Korea Society of Computer and Information
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• v.13 no.4
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• pp.79-86
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• 2008

As the rapid development of the Internet, the embedded images in HTML web pages nowadays become predominant. For its amazing function in describing the content and attracting attention, images become substantially important in web pages. All these images consist a considerable database. What's more, the semantic meanings of images are well presented by the surrounding text and links. But only a small minority of these images have precise assigned keyphrases. and manually assigning keyphrases to existing images is very laborious. Therefore it is highly desirable to automate the keyphrases extraction process. In this paper, we first introduce WWW image annotation methods, based on low level features, page tags, overall word frequency and local word frequency. Then we put forward our method of multi-cues integration image annotation. Also, show multi-cue image annotation method is more superior than other method through an experiment.

• The Journal of the Korea Contents Association
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• v.6 no.11
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• pp.266-275
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• 2006

Mostly mechanical products are connected by several components instead of single accessory in product process. Although majority of assembly process is automated, the fault analysis is not automated because it needs expert knowledge in various fields to support inclusive decision-marking. This paper proposes an assembly fault analysis support system that uses image regions which can be easily accessed and understood by experts of various fields. An assembly fault analysis support system helps effective fault analysis from assembly by integrating image regions, product design information, and fault detection information. The proposed method enables fault information access from multimedia information by segmenting product images. After product images are segmented by labeling, design information and fault information are integrated in extended Attributed Relational Graph.