• International Journal of Internet, Broadcasting and Communication
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• v.12 no.2
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• pp.21-29
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• 2020

This paper presents an effective single image haze removal using edge-preserving and adaptive transmission estimation to enhance the visibility of outdoor images vulnerable to weather and environmental conditions with computational complexity reduction. The conventional methods involve the time-consuming refinement process. The proposed transmission estimation however does not require the refinement, since it preserves the edges effectively, which selects one between the pixel-based dark channel and the patch-based dark channel in the vicinity of edges. Moreover, we propose an adaptive transmission estimation to improve the visual quality particularly in bright areas like sky. Experimental results with various hazy images represent that the proposed method is superior to the conventional methods in both subjective visual quality and computational complexity. The proposed method can be adopted to compose a haze removal module for realtime devices such as mobile devices, digital cameras, autonomous vehicles, and so on as well as PCs that have enough processing resources.

• International Journal of Internet, Broadcasting and Communication
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• v.10 no.2
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• pp.74-78
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• 2018

Recently, due to decrease hardware prices and the development of technology, analog signage has been changing to digital signage for providing content such as advertisements, videos. Furthermore, in order to provide advertisements and contents to users more effectively, technical researches are being conducted in various industries. In addition, including digital signage that uses displays, it can be seen that it provides advertisements and contents using diverse devices such as LED signage, smart pads, and smart phones. However, most digital signage is installed in one place to provide contents and provides interactivity through simple events such as manual content provision or touch. So, in this paper, we suggest a new object detection algorithm based on an adjacent frames based image correction algorithm for interactive building signage.

• International Journal of Internet, Broadcasting and Communication
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• v.11 no.1
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• pp.39-46
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• 2019

This paper proposes an adaptive threshold watershed algorithm, which is the method used for image segmentation and boundary detection, which extends the region on the basis of regional minimum point. First, apply adaptive thresholds to determine regional minimum points. Second, it extends the region by applying adaptive thresholds based on determined regional minimum points. Traditional watershed algorithms create over-segmentation, resulting in the disadvantages of breaking boundaries between regions. These segmentation results mainly from the boundary of the object, creating an inaccurate region. To solve these problems, this paper applies an improved watershed algorithm applied with adaptive threshold in regional minimum point search and region expansion in order to reduce over-segmentation and breaking the boundary of region. This resulted in over-segmentation suppression and the result of having the boundary of precisely divided regions. The experimental results show that the proposed algorithm can apply adaptive thresholds to reduce the number of segmented regions and see that the segmented boundary parts are correct.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.1
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• pp.210-218
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• 2021

CNN (Convolutional Neural Network), a type of deep learning algorithm, is a type of artificial neural network used to analyze visual images. In deep learning, it is classified as a deep neural network and is most commonly used for visual image analysis. Accordingly, an AI autonomous driving model was constructed through real-time image processing, and a crosswalk image of a road was used as an obstacle. In this paper, we proposed a low-cost model that can actually implement autonomous driving based on the CNN model. The most well-known deep neural network technique for autonomous driving is investigated and an end-to-end model is applied. In particular, it was shown that training and self-driving on a simulated road is possible through a practical approach to realizing lane detection and keeping.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.1
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• pp.269-274
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• 2023

In this paper, we proposed a new UNet 3+ model for medical image segmentation. The proposed ensemble(E) UNet 3+ model consists of UNet 3+s of varying depths into one unified architecture. UNet 3+s of varying depths have same encoder, but have their own decoders. They can bridge semantic gap between encoder and decoder nodes of UNet 3+. Deep supervision was used for learning on a total of 8 nodes of the E-UNet 3+ to improve performance. The proposed E-UNet 3+ model shows better segmentation results than those of the UNet 3+. As a result of the simulation, the E-UNet 3+ model using deep supervision was the best with loss function values of 0.8904 and 0.8562 for training and validation data. For the test data, the UNet 3+ model using deep supervision was the best with a value of 0.7406. Qualitative comparison of the simulation results shows the results of the proposed model are better than those of existing UNet 3+.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.3
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• pp.88-93
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• 2023

In the era of continuous progress, concerts have emerged as a significant medium for music performance, providing audiences with both musical enjoyment and a means of relaxation. The study examines pivotal moments and milestones in concert history, highlighting the emergence of novel elements such as visual presentations, integration of multimedia, virtual reality experiences, and metaverse concerts. By scrutinizing the repercussions of these changes on the concert experience, the study sheds light on the transformative influence of technology on concert formats, audience engagement, and artistic expression. Moreover, it delves into the challenges and opportunities arising from technological advancements in the contemporary concert landscape. The insights gained from this research contribute to a comprehensive comprehension of the dynamic interplay between technology and concert forms, thereby laying the foundation for future scholarly discourse and advancements within the field.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.2
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• pp.19-24
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• 2019

Digital technologies in the digital image field are developing and changing rapidly while creating various forms of media environments. In particular, broadcasting image-processing technologies provide more realistic images through the development of multimedia technology. Consequently, the needs of flat image quality have been nearly met, leading to technological saturation. Currently, flat images possess the advantages of popularity and freedom from visual fatigue over three-dimensional stereoscopic images. A complementary technology for flat images is the stereoscopic perception improvement technology. To examine correlations between stereoscopic perception and colour attributes for graphic images on flat displays, we have conducted experiments related to stereoscopic perception and analysed the results. In these experiments, the colour attributes of hue, value, and chroma were applied at different levels. Next, the factors that provide the highest stereoscopic perception and their interactions were analysed through analysis of variance. Finally, this study defines the significance of colour factors related to stereoscopic perception by analysing the experimental results, and proposes a colour adjustment method for improved stereoscopic perception in graphics image processing.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.3
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• pp.623-638
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• 2017

Application fields of cloud technologies have been gradually expanded with development of technology development and diversification of services. Cloud technology is used for investment efficiency, operation efficiency and service competitive advantage in digital broadcasting platform. Recently, Cloud broadcasting platform commercialized for UI(User Interface) and data broadcasting in Korea, and broadcasting service competition becomes fierce. Cloud technology of broadcasting provides remove a service dependency hardware resource and software architecture on STB device, and unified operation of user interface and service using cloud server without legacy separating management of STB types. In this paper, we explain application effects in image based cloud broadcasting service platform.

• ETRI Journal
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• v.32 no.6
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• pp.901-910
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• 2010

As a supplement to X-ray mammography, microwave imaging is a new and promising technique for breast cancer detection. Through solving the nonlinear inverse scattering problem, microwave tomography (MT) creates images from measured signals using antennas. In this paper, we describe a developed MT system and an iterative Gauss-Newton algorithm. At each iteration, this algorithm determines the updated values by solving the set of normal equations using Tikhonov regularization. Some examples of successful image reconstruction are presented.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.11 no.1
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• pp.110-115
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• 2000

A K-band GaAs MMIC receiver module has been developed using 0.15 ${\mu}{\textrm}{m}$ HEMT technology process. It incorporates two front end low noise amplifiers, a double balanced diode mixer, and filters. The RF input frequency ranges 20.1 to 21 GHz and the IF output 1.1 to 2 GHz. Test results show an overall conversion gain of more than 27 dB, and less than a 2.2 dB noise figure. The image-rejection ratio greater than 21 dB has been obtained. The isolation between RF and IF ports is better than 27 dB, and between LO and IF is more than 50 dB.