• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.25 no.5A
• /
• pp.717-725
• /
• 2000

Within the last several years, there has been a large number of algorithms developed for face recognition. The majority of these algorithms have been view- and projection-based algorithms. Our definition of projection is not restricted to projecting the image onto an orthogonal basis the definition is expansive and includes a general class of linear transformation of the image pixel values. The class includes correlation, principal component analysis, clustering, gray scale projection, and matching pursuit filters. In this paper, we perform a detailed analysis of this class of algorithms by evaluating them on the FERET database of facial images. In our experiments, a projection-based algorithms consists of three steps. The first step is done off-line and determines the new basis for the images. The bases is either set by the algorithm designer or is learned from a training set. The last two steps are on-line and perform the recognition. The second step projects an image onto the new basis and the third step recognizes a face in an with a nearest neighbor classifier. The classification is performed in the projection space. Most evaluation methods report algorithm performance on a single gallery. This does not fully capture algorithm performance. In our study, we construct set of independent galleries. This allows us to see how individual algorithm performance varies over different galleries. In addition, we report on the relative performance of the algorithms over the different galleries.

• Tunnel and Underground Space
• /
• v.26 no.1
• /
• pp.24-31
• /
• 2016

Recently, many studies have been conducted to use fixed-wing and rotary-wing unmanned aerial vehicles (UAVs, Drones) for topographic surveying in open-pit mines. Because the fixed-wing and rotary-wing UAVs have different characteristics such as flight height, speed, time and performance of mounted cameras, their results of topographic surveying at a same site need to be compared. This study selected a construction site in Yangsan-si, Gyeongsangnam-do, Korea as a study area and compared the topographic surveying results from a fixed-wing UAV (SenseFly eBee) and a popular rotary-wing UAV (DJI Phantom2 Vision+). As results of data processing for aerial photos taken from eBee and Phantom2 Vision+, orthomosaic images and digital surface models with about 4 cm grid spacing could be generated. Comparisons of the X, Y, Z-coordinates of 7 ground control points measured by differential global positioning system and those determined by eBee and Phantom2 Vision+ revealed that the root mean squared errors of X, Y, Z-coordinates were around 10 cm, respectively.

• The Korean Journal of Nuclear Medicine
• /
• v.21 no.1
• /
• pp.9-16
• /
• 1987

It is well-known that hepatic scintigraphv have been found to be less sensitive and specific in the detection of the diffuse hepatocellular diseases than that of the space-occupying lesions. To obtain the higher diagnostic specificity and sensitivity, we, using the computer quantitation, have attempted to analyze hepatic and extrahepatic $^{99m}Tc-tin$ colloid uptake patterns in various diffuse hepatocellular diseases retrospectively. The studied groups consisted of 116 cases of normal, 67 cases of acute hepatitis, 112 cases of chronic hepatitis, 61 cases of liver cirrhosis, 47 cases of fatty liver, 12 cases of hepatoma and 9 cases of metastasis, making total 424 cases. Scintigraphic imagings were obtained in the anterior, right lateral and posterior projections using high-resolution collimation, and simultaneously these gamma data were acquisited into the computer system. Both large region of interest (ROI) using light pen and ROI computer program were placed over right lobe, left lobe of liver, spleen and cardiac blood pool. Total counts in ROI were divided by the number of pixels in the ROI, and mean count rate per pixels calculated. Mean right-lobe counts were divded by mean-left lobe counts to determine right-to-left hepatic lobe ratio and mean spleen counts were divided by mean liver counts to determine spleen to liver ratio. The results were as follows. 1) Of 424 cases, 292 were male and 132 were female. The majority of age distribution was in $30\sim49$ (54.5%). 2) Inter-observer between two independant operators and inter-method between drawing by light-pen and ROI computer program variations were not significant. 3) The uptake count values (per pixel) determined at each area in normal group were $106.53{\pm}18.35$ in right lobe, $79.00{\pm}13.82$ in left lobe, $17.52{\pm}8.31$ in spleen and $8.09{\pm}3.43$ in cardiac blood pool. 4) In liver cirrhosis, right lobe uptake was decreased but spleen and cardiac blood pool uptakes were increased (p<0.01). 5) Right-to-left hepatic lobe uptake ratio was $1.37{\pm}0.24$ in normal group and significantly low in chronic hepatitis, liver cirrhosis and fatty liver, and more or less low in acute hepatitis. 6) Spleen-to-right hepatic lobe uptake ratio was $0.17{\pm}0.09$ in normal group and high in chronic hepatitis and liver cirrhosis. 7) The computer-quantitation of hepatic and extrahepatic uptake patterns thought to be sensitive and useful method in the interpretation of liver scintigram.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.28 no.2
• /
• pp.247-254
• /
• 2010

In this paper, a new approach has been studied correcting the geometric distortion of SPOT 4 imagery. Two new equations were induced by the relationship between satellite and the Earth in the space. line-of-sight (LOS) vector adjustment model for SPOT 4 imagery was implemented in this study. This model is to adjust LOS vector under the assumption that the orbital information of satellite provided by receiving station is uncertain and this uncertainty makes a constant error over the image. This model is verified using SPOT 4 satellite image with high look angle and thirty five ground points, which include 10 GCPs(Ground Control Points) and 25 check points, measured by the GPS. In total thirty five points, the geometry of satellite image calculated by given satellite information(such as satellite position, velocity, attitude and look angles, etc) from SPOT 4 satellite image was distorted with a constant error. Through out the study, it was confirmed that the LOS vector adjustment model was able to be applied to SPOT4 satellite image. Using this model, RMSEs (Root Mean Square Errors) of twenty five check points taken by increasing the number of GCPs from two to ten were less than one pixel. As a result, LOS vector adjustment model could efficiently correct the geometry of SPOT4 images with only two GCPs. This method also is expected to get good results for the different satellite images that are similar to the geometry of SPOT images.

• Journal of Biosystems Engineering
• /
• v.26 no.1
• /
• pp.21-28
• /
• 2001

Major deficiencies of current automation scheme including various robots for bioproduction include the lack of task adaptability and real time processing, low job performance for diverse tasks, and the lack of robustness of take results, high system cost, failure of the credit from the operator, and so on. This paper proposed a scheme that could solve the current limitation of task abilities of conventional computer controlled automatic system. The proposed scheme is the man-machine hybrid automation via tele-operation which can handle various bioproduction processes. And it was classified into two categories. One category was the efficient task sharing between operator and CCM(computer controlled machine). The other was the efficient interface between operator and CCM. To realize the proposed concept, task of the object identification and extraction of 3D coordinate of an object was selected. 3D coordinate information was obtained from camera calibration using camera as a measurement device. Two stereo images were obtained by moving a camera certain distance in horizontal direction normal to focal axis and by acquiring two images at different locations. Transformation matrix for camera calibration was obtained via least square error approach using specified 6 known pairs of data points in 2D image and 3D world space. 3D world coordinate was obtained from two sets of image pixel coordinates of both camera images with calibrated transformation matrix. As an interface system between operator and CCM, a touch pad screen mounted on the monitor and remotely captured imaging system were used. Object indication was done by the operator’s finger touch to the captured image using the touch pad screen. A certain size of local image processing area was specified after the touch was made. And image processing was performed with the specified local area to extract desired features of the object. An MS Windows based interface software was developed using Visual C++6.0. The software was developed with four modules such as remote image acquisiton module, task command module, local image processing module and 3D coordinate extraction module. Proposed scheme shoed the feasibility of real time processing, robust and precise object identification, and adaptability of various job and environments though selected sample tasks.

• Spatial Information Research
• /
• v.22 no.3
• /
• pp.47-58
• /
• 2014

The credible measurement, reporting and verification (MRV) is among the most critical elements in UN-REDD (United Nations programme on Reducing Emissions from Deforestation and forest Degradation in Developing Countries). This study is intended to explore MRV potential in terms of UN-REDD opportunity cost estimation using satellite image for Mt. Geum-gang of North Korea. A visual interpretation were conducted to evaluate MRV conditions by sub-dividing or decomposing the images with different pixel size into a three types of hierarchical tree structure that helps dealing with spatial variability within each subarea. The permanent record of standard satellite remote sensing system demonstrated its capability of presenting area-wide visual evidences of MRV conditions in Mt. Geum-gang (such as the identification of forested area, degradation trends for forest space, three types of hierarchical land-cover and land use tree structure, carbon density in the landscape). Satellite data could be accepted as legally binding proof when it comes to REDD opportunity cost estimation since several cases exist where remote sensing has been used as legal evidence in ICJ (International Court of Justice) and UN resolution. It doesn't seem very difficult to comply with MRV requirements for UN-REDD opportunity cost calculation due to the probative value of satellite data. It is anticipated that this research output could be used as a valuable reference for Korea-based enterprises exploring REDD project sites and the carbon traders to ensure MRV potentials using satellite image in UN-REDD Opportunity Cost estimation.

• Journal of Astronomy and Space Sciences
• /
• v.20 no.4
• /
• pp.283-298
• /
• 2003

The 2001 Leonid meteor storm has been observed all over the world, and its most intense flux since the last few decades has caused great interest among both laymen and experts. Especially, its maximum hours occurred at dawn hours of Nov. 19 in the east Asia, during which moonless clear night at the Mt. Bohyun allowed us near perfect condition of observation. Observation was carried out in the period of 01:00∼05:40(KST), which include the predicted maximum hours, with all-sky camera installed for upper atmospheric airglow research. Tn this paper we analyze 68 all-sky images obtained in this period, which contain records of 172 meteors. Utilizing the zenith hourly rate(ZHR) of 3000 and magnitude distribution index of 2, which were reported to International Meteor Organization by visible observers in the east Asia, we estimate the limiting magnitude of about 3 for meteors detected in our all-sky images. We then derive magnitudes of 83 meteors with clear pixel brightness outlines among the initially detected 172 meteors by comparing with neighbor standard stars. Angular velocities of meteors needed for computing their passing times over an all-sky image are expressed with a simple formula of an angle between a meteor head and the Leonid radiant point. The derived magnitudes of 83 meteors are in the range of -6∼-1 magnitude, and its distribution shows a maximum new -3mag. The derived magnitudes are much smaller than the limiting magnitude inferred from the comparison with the result of naked-eye observations. The difference may be due to the characteristic difference between nearly instantaneuous naked-eye observations and CCD observations with a long exposure. We redetermine magnitudes of the meteors by adjusting a meteor lasting time to be consistent with the naked-eye observations. The relative distribution of the redetermined magnitudes, which has a maximum at 0 mag., resembles that of the magnitudes determined with the in-principle method. The relative distribution is quite different from ones that decrease monotonically with decreasing magnitudes for meteors(1∼6) sensitive to naked-eye observations. We conclude from the magnitude distribution of our all-sky observation that meteors brighter than about 0 mag., appeared more frequently during the 2001 Leonid maximum hours. The frequent appearance of bright meteors has significantly important implication for meteor research. We noted, however, considerably large uncertainties in magnitudes determined only by comparing standard stars due to the unknown lasting time of meteors and the non-linear sensitivity of all-sky camera.

• Journal of Internet Computing and Services
• /
• v.16 no.2
• /
• pp.49-55
• /
• 2015

According to the statistics of traffic accidents over recent 5 years, traffic accidents during the night times happened more than the day times. There are various causes to occur traffic accidents and the one of the major causes is inappropriate or missing street lights that make driver's sight confused and causes the traffic accidents. In this paper, with smartphones, we designed and implemented a lane luminance measurement application which stores the information of driver's location, driving, and lane luminance into database in real time to figure out the inappropriate street light facilities and the area that does not have any street lights. This application is implemented under Native C/C++ environment using android NDK and it improves the operation speed than code written in Java or other languages. To measure the luminance of road, the input image with RGB color space is converted to image with YCbCr color space and Y value returns the luminance of road. The application detects the road lane and calculates the road lane luminance into the database sever. Also this application receives the road video image using smart phone's camera and improves the computational cost by allocating the ROI(Region of interest) of input images. The ROI of image is converted to Grayscale image and then applied the canny edge detector to extract the outline of lanes. After that, we applied hough line transform method to achieve the candidated lane group. The both sides of lane is selected by lane detection algorithm that utilizes the gradient of candidated lanes. When the both lanes of road are detected, we set up a triangle area with a height 20 pixels down from intersection of lanes and the luminance of road is estimated from this triangle area. Y value is calculated from the extracted each R, G, B value of pixels in the triangle. The average Y value of pixels is ranged between from 0 to 100 value to inform a luminance of road and each pixel values are represented with color between black and green. We store car location using smartphone's GPS sensor into the database server after analyzing the road lane video image with luminance of road about 60 meters ahead by wireless communication every 10 minutes. We expect that those collected road luminance information can warn drivers about safe driving or effectively improve the renovation plans of road luminance management.

• Economic and Environmental Geology
• /
• v.55 no.5
• /
• pp.551-561
• /
• 2022

Geophysical exploration methods are very useful for generating high-resolution images of underground structures, and such methods can be applied to investigation of buried cultural properties and for determining their exact locations. In this study, image feature extraction and image segmentation methods were applied to automatically distinguish the structures of buried relics from the high-resolution ground-penetrating radar (GPR) images obtained at the center of Silla Kingdom, Gyeongju, South Korea. The major purpose for image feature extraction analyses is identifying the circular features from building remains and the linear features from ancient roads and fences. Feature extraction is implemented by applying the Canny edge detection and Hough transform algorithms. We applied the Hough transforms to the edge image resulted from the Canny algorithm in order to determine the locations the target features. However, the Hough transform requires different parameter settings for each survey sector. As for image segmentation, we applied the connected element labeling algorithm and object-based image analysis using Orfeo Toolbox (OTB) in QGIS. The connected components labeled image shows the signals associated with the target buried relics are effectively connected and labeled. However, we often find multiple labels are assigned to a single structure on the given GPR data. Object-based image analysis was conducted by using a Large-Scale Mean-Shift (LSMS) image segmentation. In this analysis, a vector layer containing pixel values for each segmented polygon was estimated first and then used to build a train-validation dataset by assigning the polygons to one class associated with the buried relics and another class for the background field. With the Random Forest Classifier, we find that the polygons on the LSMS image segmentation layer can be successfully classified into the polygons of the buried relics and those of the background. Thus, we propose that these automatic classification methods applied to the GPR images of buried cultural heritage in this study can be useful to obtain consistent analyses results for planning excavation processes.

• Korean Journal of Remote Sensing
• /
• v.37 no.3
• /
• pp.543-557
• /
• 2021

Because aerosols have different spectral characteristics according to the size and composition of the particle and to the satellite sensors, a comparative analysis of aerosol products from various satellite sensors is required. In South Korea, however, a comprehensive study for the comparison of various official satellite AOD (Aerosol Optical Depth) products for a long period is not easily found. In this paper, we aimed to assess the performance of the AOD products from MODIS (Moderate Resolution Imaging Spectroradiometer), VIIRS (Visible Infrared Imaging Radiometer Suite), Himawari-8, and Sentinel-3 by referring to the AERONET (Aerosol Robotic Network) sun photometer observations for the period between January 2015 and December 2019. Seasonal and geographical characteristics of the accuracy of satellite AOD were also analyzed. The MODIS products, which were accumulated for a long time and optimized by the new MAIAC (Multiangle Implementation of Atmospheric Correction) algorithm, showed the best accuracy (CC=0.836) and were followed by the products from VIIRS and Himawari-8. On the other hand, Sentinel-3 AOD did not appear to have a good quality because it was recently launched and not sufficiently optimized yet, according to ESA (European Space Agency). The AOD of MODIS, VIIRS, and Himawari-8 did not show a significant difference in accuracy according to season and to urban vs. non-urban regions, but the mixed pixel problem was partly found in a few coastal regions. Because AOD is an essential component for atmospheric correction, the result of this study can be a reference to the future work for the atmospheric correction for the Korean CAS (Compact Advanced Satellite) series.