• Title/Summary/Keyword: 영상정보추출

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Change Detection of Land Cover Environment using Fuzzy Logic Operation : A Case Study of Anmyeon-do (퍼지논리연산을 이용한 토지피복환경 변화분석: 안면도 사례연구)

  • 장동호;지광훈;이현영
    • Korean Journal of Remote Sensing
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    • v.18 no.6
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    • pp.305-317
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    • 2002
  • The purpose of this study is to analyze the land cover environmental changes in the Anmyeon-do. Especially, it centers on the changes in the land cover environment through methods of GIS and remote sensing. The land cover environmental change areas were detected from remote sensing data, and geographic data sets related to land cover environment change were built as a spatial database in GIS. Fuzzy logic was applied for data representation and integration of thematic maps. In the natural, social, and economic environment variables, the altitude, population density, and the national land use planning showed higher fuzzy membership values, respectively. After integrating all thematic maps using fuzzy logic operation, it is possible to predict the change quantitatively. In the study area, a region where land cover change will be likely to occur is the one on a plain near the shoreline. In particular, the hills of less than 5% slope and less than 15m altitude, adjacent to the ocean, were quite vulnerable to the aggravation of coastal environment on account of current, large-scale development. In conclusions, it is expected that the generalized scheme used in this study is regarded as one of effective methodologies for land cover environmental change detection from geographic data.

Hand Motion Recognition Algorithm Using Skin Color and Center of Gravity Profile (피부색과 무게중심 프로필을 이용한 손동작 인식 알고리즘)

  • Park, Youngmin
    • The Journal of the Convergence on Culture Technology
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    • v.7 no.2
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    • pp.411-417
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    • 2021
  • The field that studies human-computer interaction is called HCI (Human-computer interaction). This field is an academic field that studies how humans and computers communicate with each other and recognize information. This study is a study on hand gesture recognition for human interaction. This study examines the problems of existing recognition methods and proposes an algorithm to improve the recognition rate. The hand region is extracted based on skin color information for the image containing the shape of the human hand, and the center of gravity profile is calculated using principal component analysis. I proposed a method to increase the recognition rate of hand gestures by comparing the obtained information with predefined shapes. We proposed a method to increase the recognition rate of hand gestures by comparing the obtained information with predefined shapes. The existing center of gravity profile has shown the result of incorrect hand gesture recognition for the deformation of the hand due to rotation, but in this study, the center of gravity profile is used and the point where the distance between the points of all contours and the center of gravity is the longest is the starting point. Thus, a robust algorithm was proposed by re-improving the center of gravity profile. No gloves or special markers attached to the sensor are used for hand gesture recognition, and a separate blue screen is not installed. For this result, find the feature vector at the nearest distance to solve the misrecognition, and obtain an appropriate threshold to distinguish between success and failure.

Roughness Analysis of Paved Road using Drone LiDAR and Images (드론 라이다와 영상에 의한 포장 노면의 평탄성 분석)

  • Jung, Kap Yong;Park, Joon Kyu
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.39 no.1
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    • pp.55-63
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    • 2021
  • The roughness of the road is an important factor directly connected to the ride comfort, and is an evaluation item for functional evaluation and pavement quality management of the road. In this study, data on the road surface were acquired using the latest 3D geospatial information construction technology of ground LiDAR, drone photogrammetry, and drone LiDAR, and the accuracy and roughness of each method were analyzed. As a result of the accuracy evaluation, the average accuracy of terrestrial LiDAR were 0.039m, 0.042m, 0.039m RMSE in X, Y, Z direction, and drone photogrammetry and drone LiDAR represent 0.072~0.076m, 0.060~0.068m RMSE, respectively. In addition, for the roughness analysis, the longitudinal and lateral slopes of the target section were extracted from the 3D geospatial information constructed by each method, and the design values were compared. As a result of roughness analysis, the ground LiDAR showed the same slope as the design value, and the drone photogrammetry and drone LiDAR showed a slight difference from the design value. Research is needed to improve the accuracy of drone photogrammetry and drone LiDAR in measurement fields such as road roughness analysis. If the usability through improved accuracy can be presented in the future, the time required for acquisition can be greatly reduced by utilizing drone photogrammetry and drone LiDAR, so it will be possible to improve related work efficiency.

Contactless User Identification System using Multi-channel Palm Images Facilitated by Triple Attention U-Net and CNN Classifier Ensemble Models

  • Kim, Inki;Kim, Beomjun;Woo, Sunghee;Gwak, Jeonghwan
    • Journal of the Korea Society of Computer and Information
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    • v.27 no.3
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    • pp.33-43
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    • 2022
  • In this paper, we propose an ensemble model facilitated by multi-channel palm images with attention U-Net models and pretrained convolutional neural networks (CNNs) for establishing a contactless palm-based user identification system using conventional inexpensive camera sensors. Attention U-Net models are used to extract the areas of interest including hands (i.e., with fingers), palms (i.e., without fingers) and palm lines, which are combined to generate three channels being ped into the ensemble classifier. Then, the proposed palm information-based user identification system predicts the class using the classifier ensemble with three outperforming pre-trained CNN models. The proposed model demonstrates that the proposed model could achieve the classification accuracy, precision, recall, F1-score of 98.60%, 98.61%, 98.61%, 98.61% respectively, which indicate that the proposed model is effective even though we are using very cheap and inexpensive image sensors. We believe that in this COVID-19 pandemic circumstances, the proposed palm-based contactless user identification system can be an alternative, with high safety and reliability, compared with currently overwhelming contact-based systems.

Liver Splitting Using 2 Points for Liver Graft Volumetry (간 이식편의 체적 예측을 위한 2점 이용 간 분리)

  • Seo, Jeong-Joo;Park, Jong-Won
    • The KIPS Transactions:PartB
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    • v.19B no.2
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    • pp.123-126
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    • 2012
  • This paper proposed a method to separate a liver into left and right liver lobes for simple and exact volumetry of the river graft at abdominal MDCT(Multi-Detector Computed Tomography) image before the living donor liver transplantation. A medical team can evaluate an accurate river graft with minimized interaction between the team and a system using this algorithm for ensuring donor's and recipient's safe. On the image of segmented liver, 2 points(PMHV: a point in Middle Hepatic Vein and PPV: a point at the beginning of right branch of Portal Vein) are selected to separate a liver into left and right liver lobes. Middle hepatic vein is automatically segmented using PMHV, and the cutting line is decided on the basis of segmented Middle Hepatic Vein. A liver is separated on connecting the cutting line and PPV. The volume and ratio of the river graft are estimated. The volume estimated using 2 points are compared with a manual volume that diagnostic radiologist processed and estimated and the weight measured during surgery to support proof of exact volume. The mean ${\pm}$ standard deviation of the differences between the actual weights and the estimated volumes was $162.38cm^3{\pm}124.39$ in the case of manual segmentation and $107.69cm^3{\pm}97.24$ in the case of 2 points method. The correlation coefficient between the actual weight and the manually estimated volume is 0.79, and the correlation coefficient between the actual weight and the volume estimated using 2 points is 0.87. After selection the 2 points, the time involved in separation a liver into left and right river lobe and volumetry of them is measured for confirmation that the algorithm can be used on real time during surgery. The mean ${\pm}$ standard deviation of the process time is $57.28sec{\pm}32.81$ per 1 data set ($149.17pages{\pm}55.92$).

A Study on the Possibility of Short-term Monitoring of Coastal Topography Changes Using GOCI-II (GOCI-II를 활용한 단기 연안지형변화 모니터링 가능성 평가 연구)

  • Lee, Jingyo;Kim, Keunyong;Ryu, Joo-Hyung
    • Korean Journal of Remote Sensing
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    • v.37 no.5_2
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    • pp.1329-1340
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    • 2021
  • The intertidal zone, which is a transitional zone between the ocean and the land, requires continuous monitoring as various changes occur rapidly due to artificial activity and natural disturbance. Monitoring of coastal topography changes using remote sensing method is evaluated to be effective in overcoming the limitations of intertidal zone accessibility and observing long-term topographic changes in intertidal zone. Most of the existing coastal topographic monitoring studies using remote sensing were conducted through high spatial resolution images such as Landsat and Sentinel. This study extracted the waterline using the NDWI from the GOCI-II (Geostationary Ocean Color Satellite-II) data, identified the changes in the intertidal area in Gyeonggi Bay according to various tidal heights, and examined the utility of DEM generation and topography altitude change observation over a short period of time. GOCI-II (249 scenes), Sentinel-2A/B (39 scenes), Landsat 8 OLI (7 scenes) images were obtained around Gyeonggi Bay from October 8, 2020 to August 16, 2021. If generating intertidal area DEM, Sentinel and Landsat images required at least 3 months to 1 year of data collection, but the GOCI-II satellite was able to generate intertidal area DEM in Gyeonggi Bay using only one day of data according to tidal heights, and the topography altitude was also observed through exposure frequency. When observing coastal topography changes using the GOCI-II satellite, it would be a good idea to detect topography changes early through a short cycle and to accurately interpolate and utilize insufficient spatial resolutions using multi-remote sensing data of high resolution. Based on the above results, it is expected that it will be possible to quickly provide information necessary for the latest topographic map and coastal management of the Korean Peninsula by expanding the research area and developing technologies that can be automatically analyzed and detected.

The Remote Sensing Algorithm for Analysis of Suspended Sediments Distribution in Lake Sihwa and Coastal Area (시화호와 연안해역의 부유사 분포 분석을 위한 원격탐사 알고리듬)

  • Jeong, Jongchul;Yoo, Sinjae;Kim, Jungwook
    • Journal of the Korean Association of Geographic Information Studies
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    • v.2 no.2
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    • pp.59-68
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    • 1999
  • The study for detecting suspended sediment distribution in Lake Sihwa, which has a large surface area and coastal area, using remote sensing technique was carried out with development of satellite data collected since 1970. The research, however, analysis of spatial distribution and quantity, is not common in domestic study and useful algorithms have not been proposed. In this study, a suspended sediment algorithm was composed with in-situ data obtained in study area and remote sensing reflectance obtained in-water optical instrument, which has SeaWiFS wavelength bands. However, when the algorithm was applied to Landsat TM data, including an in-situ data set, and some problems arose. The composition of the algorithm which was structured with band difference and band ratio showed the correlation of $R^2$=0.7649 with concentration of suspended sediments. And, between calculated and observed concentration of suspended sediments there was a correlation of $R^2$=0.6959. However, remote sensing reflectance obtained from Landsat TM is not good for the estimation of concentration of suspended sediments, because of high concentration of chlorophyll and CDOM(colored dissolved organic matter).

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Analysis on the Characteristics of Heat Wave Vulnerable Areas Using Landsat 8 Data and Vulnerability Assessment Analysis (Landsat 8 영상과 취약성 분석을 활용한 폭염재해 취약지역의 특성분석)

  • KIM, Ji-Sook;KIM, Ho-Yong
    • Journal of the Korean Association of Geographic Information Studies
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    • v.23 no.1
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    • pp.1-14
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    • 2020
  • Cities are highly susceptible to disasters due to concentration of population and infrastructure and intensive land use, and there are various factors that affect vulnerability according to regional characteristics. This study analyzed the vulnerability of the heat wave and the surface temperature extracted from Landsat 8 satellite data. Areas with high surface temperature and with high vulnerability did not match. This study overlaid the results of vulnerability analysis and the land surface temperature(LST) in order to identify causes of vulnerability. The results showed that some areas within high-density commercial and semi-residential areas were the most vulnerable, with climate exposure factors, the ratio of the vulnerable populations and residential defective areas being the main causes. Accordingly, alternatives such as green space and residential environmental improvement could be suggested. Various policies for reducing and adapting to heat wave have been established and implemented. However, it is necessary to examine the regional and spatial characteristics of the city, to accurately diagnose the cause of the heat wave, and to prepare appropriate long-term alternatives accordingly.

Fast Coding Unit Decision Algorithm Based on Region of Interest by Motion Vector in HEVC (움직임 벡터에 의한 관심영역 기반의 HEVC 고속 부호화 유닛 결정 방법)

  • Hwang, In Seo;Sunwoo, Myung Hoon
    • Journal of the Institute of Electronics and Information Engineers
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    • v.53 no.11
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    • pp.41-47
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    • 2016
  • High efficiency video coding (HEVC) employs a coding tree unit (CTU) to improve the coding efficiency. A CTU consists of coding units (CU), prediction units (PU), and transform units (TU). All possible block partitions should be performed on each depth level to obtain the best combination of CUs, PUs, and TUs. To reduce the complexity of block partitioning process, this paper proposes the PU mode skip algorithm with region of interest (RoI) selection using motion vector. In addition, this paper presents the CU depth level skip algorithm using the co-located block information in the previously encoded frames. First, the RoI selection algorithm distinguishes between dynamic CTUs and static CTUs and then, asymmetric motion partitioning (AMP) blocks are skipped in the static CTUs. Second, the depth level skip algorithm predicts the most probable target depth level from average depth in one CTU. The experimental results show that the proposed fast CU decision algorithm can reduce the total encoding time up to 44.8% compared to the HEVC test model (HM) 14.0 reference software encoder. Moreover, the proposed algorithm shows only 2.5% Bjontegaard delta bit rate (BDBR) loss.

Analysis of Urban Thermal Environment for Environment-Friendly Spatial Plan (친환경적 공간계획을 위한 도시의 열환경 분석)

  • Lee, Woo-Sung;Jung, Sung-Gwan;Park, Kyung-Hun;Kim, Kyung-Tae
    • Journal of the Korean Association of Geographic Information Studies
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    • v.13 no.1
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    • pp.142-154
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    • 2010
  • The purpose of this study is to analyze the effects of various spatial characteristics on the land surface temperature and to grasp the characteristics of thermal environment by types of urban area in Changwon, Gyeongsangnam-do. The spatial data were consisted LST, normalized difference built-up index(NDBI) and normalized difference vegetation index(NDVI) obtained from Landsat 5 TM and land use and land cover map classified from high resolution digital aerial photograph($10cm{\times}10cm$). The unit space for spatial analysis was built by $500m{\times}500m$ Vector GRID. According to the results of estimation of relationship between thermal environment and spatial characteristics, LST had the highest positive correlation with NDBI by 0.929 and had high positive correlation with impervious area ratio by 0.857. In order to analysis of thermal environment on land use, types of urban area were classified by 4 of residential focus area, industrial focus area, green focus area and mixed area. According to the results of analysis, mean LST of industrial focus area was showed the highest by $21.10^{\circ}C$. But mean LST of green focus area was analyzed the lowest by $18.85^{\circ}C$. In conclusion, the results of this study investigated the effects of spatial characteristics on urban thermal environment and can provide methods and basic informations about land use planning and development density restriction for reduction of urban heat.