• Journal of Korea Society of Industrial Information Systems
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• v.14 no.1
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• pp.1-8
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• 2009

The objective of this study is to design a system that automatically monitors the state of interior spaces like offices where lots of people are coming and going through image data and environment data, which includes temperature, humidity, and other conditions, and implement and test related application programs. In practice, there are lots of image data automatically obtained by unmanned equipments, such as certain types of CCTVs, for monitoring situation in usual interior spaces. This image data can be used as a more effective manner by establishing a system that recognizes situation in specific interior spaces based on the relationship between image and environment data. For instance, it is possible to perform unmanned on/off controls for various electronic equipments, such as air conditioners, lights, and other devices, through analyzing the data acquisited from environment sensors (temperature, humidity, and illumination) as dynamic states are not maintained for a specified period of time. For implementing these controls, this study analyzes environment data acquisited from temperature and humidity sensors and image data input from wireless cameras to recognize situation and that can be used to automatically control environment variables configured by users. Experiments were applied in a laboratory where unmanned controls were effectively performed as automatic on/off controls for the air conditioner and lights installed in the laboratory as certain motions were detected or undetected for a specified period of time.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.1
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• pp.225-231
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• 2013

In this study, we propose the design of optimized pRBFNNs-based night vision face recognition system using PCA algorithm. It is difficalt to obtain images using CCD camera due to low brightness under surround condition without lighting. The quality of the images distorted by low illuminance is improved by using night vision camera and histogram equalization. Ada-Boost algorithm also is used for the detection of face image between face and non-face image area. The dimension of the obtained image data is reduced to low dimension using PCA method. Also we introduce the pRBFNNs as recognition module. The proposed pRBFNNs consists of three functional modules such as the condition part, the conclusion part, and the inference part. In the condition part of fuzzy rules, input space is partitioned by using Fuzzy C-Means clustering. In the conclusion part of rules, the connection weights of pRBFNNs is represented as three kinds of polynomials such as linear, quadratic, and modified quadratic. The essential design parameters of the networks are optimized by means of Differential Evolution.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2022.11a
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• pp.187-190
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• 2022

본 논문은 메타버스 등 인공지능 연계 증강/가상현실 부동 중계 플랫폼에서 부동산 영상 기반 매물 소개 시스템 구축에서 사생활 및 개인정보가 영상에 담기게 될 수 있는 위험이 존재하기에 부동산 영상 내의 개인정보 및 민감 정보를 인공지능 기술을 기반으로 검출하여 삭제해주고 복원해주는 인공지능 기술 연구개발을 목표로 하였다. 한국형 부동산 내 민감 object 를 정의하고, 최신 인공지능 딥러닝 기술 기반 민감 object detection 알고리즘을 연구 개발하며, 영상에서 삭제된 부분은 인공지능 기술을 기반으로 물체가 없는 실제 공간영상으로 복원해주는 영상복원 기술도 연구 개발하였다. 한국형 부동산 환경 (영상 촬영 조도, 디스플레이 스타일, 주변 가구 배치 등)에 맞는 인공지능 모델 구축을 위하여, 자체적으로 한국 영상 database 구축 및 Transfer learning for target domain adaptation 을 진행하였다. 제안된 알고리즘은 일반적인 환경에서 98%의 정확도와 challenge 환경에서 (occlusion 빛 반사, 저조도 등) 81%의 정확도를 보였다. 본 기술은 Proptech 분야에서 주목받고 있는 메타버스 기반 온라인 중계 서비스 기술을 활성화하기 위하여 기획되었으며, 특히 메타버스 부동산 중계 플랫폼의 활성화를 위하여 사생활 보호 측면에서 필요한 중요 기술을 인공지능 기술을 활용하여 연구 개발하였다.

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