• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1018-1020
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• 2003

The costal area where takes up over 32% in domestic teritory is considered as very importantly because it has not only economic facilities such as harbor and an industrial complex but also recreation facilities. Moreover, the tidal flat area has been used as culture ponds and salt farms because this area is occupied by various oceanic species. Also, the tidal flat area has played an important role to purify ocean pollution and maintain an ecosystem. However, the costal ecosystem has seriously threatened by domestic reclamation projects and a large-scale tide embankment during recent 10 years in Korea. This serious problem results in loosing 34%(810$km^2$) of the entire domestic costal area. In this paper, the micro-landform in the tidal flat area, which is called as Garolim bay in Korea, is classified by using Landsat TM images also verified through a filed report. Through the result of this, the tidal flat area is expected to manage efficiently especially through analyzing sediment environment and characteristic of grain size by using satellite images.

• Journal of the Semiconductor & Display Technology
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• v.20 no.2
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• pp.126-130
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• 2021

The ball grid array is one of the packaging methods that used in high density printed circuit board. Solder void defects caused by voids in the solder ball during the BGA process do not directly affect the reliability of the product, but it may accelerate the aging of the device on the PCB layer or interface surface depending on its size or location. Void inspection is important because it is related in yields with products. The most important process in the optical inspection of solder void is the segmentation process of solder and void. However, there are several segmentation algorithms for the vision inspection, it is impossible to inspect all of images ideally. When X-Ray images with poor contrast and high level of noise become difficult to perform image processing for vision inspection in terms of software programming. This paper suggests the solution to deal with the suggested problem by means of using Mask R-CNN instead of digital image processing algorithm. Mask R-CNN model can be trained with images pre-processed to increase contrast or alleviate noises. With this process, it provides more efficient system about complex object segmentation than conventional system.

• Journal of Koreanology Reviews
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• v.1 no.1
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• pp.31-36
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• 2022

Recently, as the status of South Korean popular culture has risen, the Korean Wave is gaining popularity not only in Asia but also in Europe, America, and South America, and is currently at the center of the global cultural phenomena. Among them, in particular, the cultural content industry has been developing rapidly thanks to the Korean Wave. Currently, the Korean Wave is spreading all over the world while bringing about positive effects to South Korea. In fact, until 2017, political and social issues such as 'North Korea/North Korean nuclear weapons' and 'Korean War' were considered as the images associated with South Korea, but from 2018, it has been shown that all images associated with South Korea are cultural content except for 'IT industry'. Given the economic effects that can be obtained not only from the positive associated images of South Korea per se but also from the complex action with various industries in South Korea, the craze for the Korean Wave can be viewed as affecting the overall national prestige of South Korea. For the steady vogue of the Korean Wave, thorough investigation of the Korean Wave and understanding of the expectations of consumers of the Korean Wave seem to be necessary

• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.3
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• pp.213-220
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• 2023

Face recognition is a very important process in video monitoring and is a type of biometric technology. It is mainly used for identification and security purposes, such as ID cards, licenses, and passports. The recognition process has many variables and is complex, so development has been slow. In this paper, we proposed a face recognition method using CNN, which has been re-examined due to the recent development of computers and algorithms, and compared with the feature comparison method, which is an existing face recognition algorithm, to verify performance. The proposed face search method is divided into a face region extraction step and a learning step. For learning, face images were standardized to 50×50 pixels, and learning was conducted while minimizing unnecessary nodes. In this paper, convolution and polling-based techniques, which are one of the deep learning technologies, were used for learning, and 1,000 face images were randomly selected from among 7,000 images of Caltech, and as a result of inspection, the final recognition rate was 98%.

• Economic and Environmental Geology
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• v.56 no.4
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• pp.397-408
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• 2023

A total of 64 specimens of trace fossils were collected from the Jinju Formation of the construction site of Jinju Aviation Industrial Complex, and from the Haman Formation of Namhae Gain-ri fossil site. The fossils are continuously and regularly meandering sine-curve in shape. The fossil varies in morphology: width between 0.2 and 5.6 mm, wavelength between 1.5 and 28 mm, and amplitude between 0.9 and 7.9 mm; the Jinju specimens are commonly wider than the Haman ones. The ratio of wavelength to amplitude is more or less regular regardless of width of the specimen, and the linear correlation of the ratios shows that the Jinju specimens fit better than the Haman specimens. Taking all morphometric parameters, specimens in all size ranges are temporarily identified as ichnospecies Cochlichnus anguineus. In order to obtain more distinct and clearer images of Cochlichnus, we selected two specimens and applied a new imaging technology RTI. For photography of the trace fossils, 50 to 80 images were taken per set with photometric lighting close to the surface and horizontally. RTI technology clearly showed that the images of tiny fossils were improved: the surface contrast become sharper and messy and unnecessary information disappeared. Currently, RTI technology is used in many fields including preservation of cultural properties and archaeology. As a consequence, we hope to apply this technique to the field of paleontology, especially to the study of trace fossils of very small size.

• Journal of Information Processing Systems
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• v.19 no.4
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• pp.427-438
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• 2023

Plenty of works have indicated that single image super-resolution (SISR) models relying on synthetic datasets are difficult to be applied to real scene text image super-resolution (STISR) for its more complex degradation. The up-to-date dataset for realistic STISR is called TextZoom, while the current methods trained on this dataset have not considered the effect of multi-scale features of text images. In this paper, a multi-scale and attention fusion model for realistic STISR is proposed. The multi-scale learning mechanism is introduced to acquire sophisticated feature representations of text images; The spatial and channel attentions are introduced to capture the local information and inter-channel interaction information of text images; At last, this paper designs a multi-scale residual attention module by skillfully fusing multi-scale learning and attention mechanisms. The experiments on TextZoom demonstrate that the model proposed increases scene text recognition's (ASTER) average recognition accuracy by 1.2% compared to text super-resolution network.

• Journal of KIISE:Computer Systems and Theory
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• v.32 no.1
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• pp.1-8
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• 2005

Image morphing to generate 2D transitions between images may be difficult even to express simple 3D transformations. In addition, previous view morphing method requires control points for postwarping, and is much affected by self- occlusion. This paper presents a new morphing algorithm that can generate automatically in-between scenes from un-calibrated images. Our algorithm rectifies input images based on the fundamental matrix, which is followed by linear interpolation with bilinear disparity map. In final, we generate in-between views by inverse mapping of homography between the rectified images. The proposed method nay be applied to photographs and drawings, because neither knowledge of 3D shape nor camera calibration, which is complex process generally, is required. The generated in-between views can be used in various application areas such as simulation system of virtual environment and image communication.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.6
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• pp.2480-2496
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• 2020

Considering that high-dose X-ray radiation during CT scans may bring potential risks to patients, in the medical imaging industry there has been increasing emphasis on low-dose CT. Due to complex statistical characteristics of noise found in low-dose CT images, many traditional methods are difficult to preserve structural details effectively while suppressing noise and artifacts. Inspired by the deep learning techniques, we propose a densely connected residual network (DCRN) for low-dose CT image noise cancelation, which combines the ideas of dense connection with residual learning. On one hand, dense connection maximizes information flow between layers in the network, which is beneficial to maintain structural details when denoising images. On the other hand, residual learning paired with batch normalization would allow for decreased training speed and better noise reduction performance in images. The experiments are performed on the 100 CT images selected from a public medical dataset-TCIA(The Cancer Imaging Archive). Compared with the other three competitive denoising algorithms, both subjective visual effect and objective evaluation indexes which include PSNR, RMSE, MAE and SSIM show that the proposed network can improve LDCT images quality more effectively while maintaining a low computational cost. In the objective evaluation indexes, the highest PSNR 33.67, RMSE 5.659, MAE 1.965 and SSIM 0.9434 are achieved by the proposed method. Especially for RMSE, compare with the best performing algorithm in the comparison algorithms, the proposed network increases it by 7 percentage points.

• Journal of the Korea Society of Computer and Information
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• v.13 no.4
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• pp.97-103
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• 2008

This study is to present a fainting motion recognizing method by using fish-eye lens images to sense emergency situations. The camera with fish-eye lens located at the center of the ceiling of the living room sends images, and then the foreground pixels are extracted by means of the adaptive background modeling method based on the Gaussian complex model, which is followed by tracing of outer points in the foreground pixel area and the elliptical mapping. During the elliptical tracing, the fish-eye lens images are converted to fluoroscope images. the size and location changes, and moving speed information are extracted to judge whether the movement, pause, and motion are similar to fainting motion. The results show that compared to using fish-eye lens image, extraction of the size and location changes. and moving speed by means of the conversed fluoroscope images has good recognition rates.

• Journal of Periodontal and Implant Science
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• v.47 no.1
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• pp.30-40
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• 2017

Purpose: Optical coherence tomography (OCT) is a noninvasive diagnostic technique that may be useful for both qualitative and quantitative analyses of the periodontium. Micro-computed tomography (micro-CT) is another noninvasive imaging technique capable of providing submicron spatial resolution. The purpose of this study was to present periodontal images obtained using ex vivo dental OCT and to compare OCT images with micro-CT images and histologic sections. Methods: Images of ex vivo canine periodontal structures were obtained using OCT. Biologic depth measurements made using OCT were compared to measurements made on histologic sections prepared from the same sites. Visual comparisons were made among OCT, micro-CT, and histologic sections to evaluate whether anatomical details were accurately revealed by OCT. Results: The periodontal tissue contour, gingival sulcus, and the presence of supragingival and subgingival calculus could be visualized using OCT. OCT was able to depict the surface topography of the dentogingival complex with higher resolution than micro-CT, but the imaging depth was typically limited to 1.2-1.5 mm. Biologic depth measurements made using OCT were a mean of 0.51 mm shallower than the histologic measurements. Conclusions: Dental OCT as used in this study was able to generate high-resolution, cross-sectional images of the superficial portions of periodontal structures. Improvements in imaging depth and the development of an intraoral sensor are likely to make OCT a useful technique for periodontal applications.