• Tunnel and Underground Space
• /
• v.34 no.3
• /
• pp.208-217
• /
• 2024

There is so much research effort for developing and implementing deep learning-based surveillance systems to manage health and safety issues in construction sites. Especially, the development of deep learning-based object detection in various environmental changes has been progressing because those affect decreasing searching performance of the model. Among the various environmental variables, the accuracy of the object detection model is significantly dropped under low illuminance, and consistent object detection accuracy cannot be secured even the model is trained using low-light images. Accordingly, there is a need of low-light enhancement to keep the performance under low illuminance. Therefore, this paper conducts a comparative study of various deep learning-based low-light image enhancement models (GLADNet, KinD, LLFlow, Zero-DCE) using the acquired construction site image data. The low-light enhanced image was visually verified, and it was quantitatively analyzed by adopting image quality evaluation metrics such as PSNR, SSIM, Delta-E. As a result of the experiment, the low-light image enhancement performance of GLADNet showed excellent results in quantitative and qualitative evaluation, and it was analyzed to be suitable as a low-light image enhancement model. If the low-light image enhancement technique is applied as an image preprocessing to the deep learning-based object detection model in the future, it is expected to secure consistent object detection performance in a low-light environment.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.42 no.5
• /
• pp.741-749
• /
• 2022

Major space agencies are planning for the rover-based lunar exploration since water-ice was detected in permanently shadowed regions (PSR). Although sunlight does not directly reach the PSRs, it is expected that reflected sunlight sustains a certain level of low-light environment. In this research, the indoor testbed was made to simulate the PSR's lighting and topological conditions, to which low light enhancement methods (CLAHE, Dehaze, RetinexNet, GLADNet) were applied to restore image brightness and color as well as to investigate their influences on the performance of feature extraction and matching methods (SIFT, SURF, ORB, AKAZE). The experiment results show that GLADNet and Dehaze images in order significantly improve image brightness and color. However, the performance of the feature extraction and matching methods were improved by Dehaze and GLADNet images in order, especially for ORB and AKAZE. Thus, in the lunar exploration, Dehaze is appropriate for building 3D topographic map whereas GLADNet is adequate for geological investigation.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2022.05a
• /
• pp.443-445
• /
• 2022

광원 자체의 밝기가 낮거나 드리워진 그림자 등의 이유로 어두운 영역을 포함하고 있는 저조도 영상으로 인해 물체의 식별이 어려운 상황을 일상생활에서 겪게 된다. 본 논문에서는 조명 성분의 영향을 줄이고 객체의 특징을 표현하는 반사 성분을 강조하여 화질을 개선한다. 또한 촬영하는 카메라와 영상의 물체 사이의 상대적인 움직임으로 발생하는 흐릿한 영역을 최대한 제거해주고 잡음까지 보정이 되는 Stack-attention 기법을 제안한다.

• The Journal of the Korea Contents Association
• /
• v.20 no.8
• /
• pp.114-127
• /
• 2020

The online performance market is increasing due to recent pandemic events. However, due to the short introduction time of domestic online performances, there is a lack of related prior studies or success stories. In addition, most of these projects are short-lived projects or poor profits, so it is necessary to study how to activate them. The Sac on Screen project, which has been in progress since 10 years ago, has its own imaging experience, and the screening works and screening venues are also diverse, so it is an object of study. In addition, since annual satisfaction surveys are conducted, the business was evaluated based on the voice of customers from the data of the past three years. Based on the analyzed results, a free and paid version of the business model canvas was drawn through a group of experts. As a result of this synthesis, the following major implications were drawn. First, expanding research on online performances, second, needing a sense of responsibility for quality management of content, third, increasing diversity in content selection, and fourth, enhancing the liveliness of online performances, Fifth, efforts are needed to attract private investment and develop value-added products.