• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제17권4호
• /
• pp.1049-1065
• /
• 2023

Recently, with the development of IoT, AI, and mobile terminals, medical information platforms are expanding. The medical information platform can determine a patient's emergency situation, and medical staff can easily access patient information through a mobile terminal. However, in the existing platform, emergency situation decision is delayed, and faster and stronger authentication is required in emergency situations. Therefore, we propose an edge computing-based medical information platform for automatic authentication using patient situations. We design an edge computing-based medical information platform architecture capable of rapid transmission of biometric data of IoT and quick emergency situation decision, and implement the platform data flow in emergency situations. Relying on this platform, we propose the automatic authentication using patient situations. The automatic authentication protects patient information through patient-centered authentication by using the patient's situation as an authentication factor, and enables quick authentication by automatically proceeding with mobile terminal authentication after user authentication in emergencies without user intervention. We compared the proposed platform with existing platforms to show that it can make quick and stable emergency decisions. In addition, comparing the automatic authentication with existing authentication showed that it is fast and protects medical information centered on patient situations in emergency situations.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제5권11호
• /
• pp.2068-2086
• /
• 2011

Based on the quincunx sub-sampling grid, the New Interleaved Hierarchical INTerpolation (NIHINT) method is recognized as a superior pyramid data structure for the lossless and progressive coding of natural images. In this paper, we propose a new image interpolation algorithm, Edge Adaptive Hierarchical INTerpolation (EAHINT), for a further reduction in the entropy of interpolation errors. We compute the local variance of the causal context to model the strength of a local edge around a target pixel and then apply three statistical decision rules to classify the local edge into a strong edge, a weak edge, or a medium edge. According to these local edge types, we apply an interpolation method to the target pixel using a one-directional interpolator for a strong edge, a multi-directional adaptive weighting interpolator for a medium edge, or a non-directional static weighting linear interpolator for a weak edge. Experimental results show that the proposed algorithm achieves a better compression bit rate than the NIHINT method for lossless image coding. It is shown that the compression bit rate is much better for images that are rich in directional edges and textures. Our algorithm also shows better rate-distortion performance and visual quality for progressive image transmission.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제14권12호
• /
• pp.4682-4705
• /
• 2020

The Unmanned Aerial Vehicles (UAV) networks consisting of low-cost UAVs are very vulnerable to smart jammers that can choose their jamming policies based on the ongoing communication policies accordingly. In this article, we propose a novel cloud and edge-aided mobile communication scheme for low-cost UAV network against smart jamming. The challenge of this problem is to design a communication scheme that not only meets the requirements of defending against smart jamming attack, but also can be deployed on low-cost UAV platforms. In addition, related studies neglect the problem of decision-making algorithm failure caused by intermittent ground-to-air communication. In this scheme, we use the policy network deployed on the cloud and edge servers to generate an emergency policy tables, and regularly update the generated policy table to the UAVs to solve the decision-making problem when communications are interrupted. In the operation of this communication scheme, UAVs need to offload massive computing tasks to the cloud or the edge servers. In order to prevent these computing tasks from being offloaded to a single computing resource, we deployed a lightweight game algorithm to ensure that the three types of computing resources, namely local, edge and cloud, can maximize their effectiveness. The simulation results show that our communication scheme has only a small decrease in the SINR of UAVs network in the case of momentary communication interruption, and the SINR performance of our algorithm is higher than that of the original Q-learning algorithm.

• 방송공학회논문지
• /
• 제13권3호
• /
• pp.310-318
• /
• 2008

H.264/AVC는 각 매크로블록에 대해서 최적의 부호화 모드와 참조 프레임을 결정해 주는 RDO (Rate-Distortion Optimization) 기법을 사용하여 기존의 비디오 압축 표준보다 더 좋은 부호화 효율을 얻고 있다. 하지만, RDO 기법은 하나의 매크로블록 모드를 결정할 때마다, 다양한 블록 타입의 화면내 (Intra) 예측을 수행하고 화면간 (Inter) 예측에 대해서도 1/4 화소까지 고려하는 움직임 추정(Motion Estimation)을 수행한 후 발생되는 비트까지 고려하여 최적의 모드를 결정하기 때문에 부호화기의 복잡도가 매우 큰 문제점이 있다. 따라서 영상의 객관적 화질은 유지하면서 부호화기의 복잡도를 낮추기 위한 많은 고속 알고리즘들이 제안되었고 연구 중에 있다. 본 논문에서는, 역 트리 구조의 경계 방향 예측 알고리즘을 이용한 고속 화면내 모드 결정 기법을 제안한다. 제안된 방법은 $4{\times}4$ 블록의 지역 경계 정보를 이용하여 해당 블록의 DE (Dominant Edge)를 찾아내고 DE에 상응하는 화면내 모드를 이용하여 RDO를 수행한다 $8{\times}8$ 블록 (또는 $16{\times}16$ 블록)의 DE는 이전 단계 4개의 $4{\times}4$ 블록 (또는 $8{\times}8$ 블록) DE들로부터 계산되고, 이 단계에서의 RDO 또한 DE에 상응하는 화면내 모드를 이용한다. 실험결과 제안 방법은 화면내 부호화에 사용되는 후보 모드의 수를 줄임으로써 JM12.2와 비교하여 화면내 부호화 시간을 평균 64% 단축시킬 수 있었다.

• 한국방송∙미디어공학회:학술대회논문집
• /
• 한국방송공학회 2013년도 하계학술대회
• /
• pp.180-181
• /
• 2013

High efficiency video coding (HEVC) appears due to the demand on high compression video coding beyond H.264/AVC in ultra-high definition (UHD) videos. As for intra prediction, HEVC has 35 prediction modes while H.264/AVC has 9 intra modes. To exploit the spatial correlation, we adopt an edge detection method, establish the edge map, and adaptively select the candidate modes using the acquired edge information in a block. The number of the candidate modes is determined through trade-off between computational complexity and coding efficiency. Besides, the range of coding unit sizes is determined using the uniqueness of the edge directions for the given image block. As a result, we reduced the encoding time by 56.8% at the cost of 2.5% BD-BR increase on average compared to Full modes at the HEVC reference software (HM 6.0 [1]).

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• 제12권4호
• /
• pp.308-318
• /
• 2012

Captions include information which relates to the images. In order to obtain the information in the captions, text extraction methods from images have been developed. However, most existing methods can be applied to captions with a fixed height or stroke width using fixed pixel-size or block-size operators which are derived from morphological supposition. We propose an edge connected components based method that can extract Korean captions that are composed of various sizes and fonts. We analyze the properties of edge connected components embedding captions and build a decision tree which discriminates edge connected components which include captions from ones which do not. The images for the experiment are collected from broadcast programs such as documentaries and news programs which include captions with various heights and fonts. We evaluate our proposed method by comparing the performance of the latent caption area extraction. The experiment shows that the proposed method can efficiently extract various sizes of Korean captions.

• 한국정보통신학회논문지
• /
• 제24권1호
• /
• pp.138-140
• /
• 2020

As the IoT is applied to home and industrial networks, data generated by the IoT is being processed at the cloud edge. Intrusion detection function is very important because it can be operated by invading IoT devices through the cloud edge. Data delivered to the edge network in the cloud environment is traffic at the application layer. In order to determine the intrusion of the packet transmitted to the IoT, the intrusion should be detected at the application layer. This paper proposes the intrusion detection function at the application layer excluding normal traffic from IoT intrusion detection function. As the proposed method, we obtained the intrusion detection result by decision tree method and explained the detection result for each feature.

• 한국컴퓨터산업학회논문지
• /
• 제4권10호
• /
• pp.643-654
• /
• 2003

택타일 영상을 사용하여 로봇 그리퍼 내부 작업 물체의 미끄럼 및 회전을 감지하는 기법을 제안해 본다. 기존에 제안된 모우멘트 불변량 사용방법의 경우 택셀 수 변화가 발생하는 경우 적용 할 수 없는 단점을 가지고 있다. 에지 ＆ 라인 불변량 특성을 이용한 경우 기본적으로 특정수 이상의 택셀을 가지고 있어야 하므로 택셀수가 적은 경우 적용 할 수 없다. 이 같은 문제점을 해결하기 위하여 택셀 영상을 분석하고 적용기법 결정인자를 추출한다. 이를 이용하여 필터링 문턱값을 설정하여 택타일 영상을 필터링하고, 결정인자에 따라 모우멘트 불변량 사용방법과 에지 ＆ 라인 불변량 사용 방법 중 적합한 기법을 채택하는 새로운 방법을 제안한다 컴퓨터 모의 실험과 하드웨어 실험에 적용한 결과 개선된 이동 및 회전 등 움직임 감지가 가능하였다.

• 한국정보통신학회:학술대회논문집
• /
• 한국해양정보통신학회 2002년도 추계종합학술대회
• /
• pp.804-807
• /
• 2002

영상의 에지는 입력 영상에 대한 많은 정보들을 가지고 있다. 에지 검출을 이용하는 많은 응용들이 있으며, 다양한 특수 효과들을 위해 사용되기도 한다. 에지 검출은 영상 분석의 한 분야로서 영상분할은 영상의 구성을 결정하기 위해서 화소들을 하나의 영역으로 만들기 위해 사용된다. 본 논문에서는 영상분할을 위한 에지검출의 다양한 방법들을 통한 영상분할을 하였다. 먼저 영상의 특징을 분석하고 각 영상의 특징에 따라 에지검출의 방법을 선택적으로 채택하도록 하여 영상특징을 추출하였다. 언어의 특징을 고려하여 Java를 이용한 영상분할을 통해 효율적인 에지 검출기를 구현하였다.

• International Journal of Automotive Technology
• /
• 제6권2호
• /
• pp.171-181
• /
• 2005

The purpose of this paper is two-fold: 1) A novel algorithm in order to extract lane-related information from road images is presented; 2) Design specifications of an image processing onboard unit capable of extracting lane­related information in real-time is also presented. Obtaining precise information from road images requires many features due to the effects of noise that eventually leads to long processing time. By exploiting a FPGA and DSP, we solve the problem of real-time processing. Due to the fact that image processing of road images relies largely on edge features, the FPGA is adopted in the hardware design. The schematic configuration of the FPGA is optimized in order to perform 3 $\times$ 3 Sobel edge extraction. The DSP carries out high-level image processing of recognition, decision, estimation, etc. The proposed algorithm uses edge features to define an Edge Distribution Function (EDF), which is a histogram of edge magnitude with respect to the edge orientation angle. The EDF enables the edge-related information and lane-related to be connected. The performance of the proposed system is verified through the extraction of lane-related information. The experimental results show the robustness of the proposed algorithm and a processing speed of more than 25 frames per second, which is considered quite successful.