• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1505-1514
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• 2022

Image matching is a crucial preprocessing step for effective utilization of multi-temporal and multi-sensor very high resolution (VHR) satellite images. Deep learning (DL) method which is attracting widespread interest has proven to be an efficient approach to measure the similarity between image pairs in quick and accurate manner by extracting complex and detailed features from satellite images. However, Image matching of VHR satellite images remains challenging due to limitations of DL models in which the results are depending on the quantity and quality of training dataset, as well as the difficulty of creating training dataset with VHR satellite images. Therefore, this study examines the feasibility of DL-based method in matching pair extraction which is the most time-consuming process during image registration. This paper also aims to analyze factors that affect the accuracy based on the configuration of training dataset, when developing training dataset from existing multi-sensor VHR image database with bias for DL-based image matching. For this purpose, the generated training dataset were composed of correct matching pairs and incorrect matching pairs by assigning true and false labels to image pairs extracted using a grid-based Scale Invariant Feature Transform (SIFT) algorithm for a total of 12 multi-temporal and multi-sensor VHR images. The Siamese convolutional neural network (SCNN), proposed for matching pair extraction on constructed training dataset, proceeds with model learning and measures similarities by passing two images in parallel to the two identical convolutional neural network structures. The results from this study confirm that data acquired from VHR satellite image database can be used as DL training dataset and indicate the potential to improve efficiency of the matching process by appropriate configuration of multi-sensor images. DL-based image matching techniques using multi-sensor VHR satellite images are expected to replace existing manual-based feature extraction methods based on its stable performance, thus further develop into an integrated DL-based image registration framework.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1309-1320
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• 2023

The technological development and popularization of mobile devices have developed so that users can check their location anywhere and use the Internet. However, in the case of indoors, the Internet can be used smoothly, but the global positioning system (GPS) function is difficult to use. There is an increasing need to provide real-time location information in shaded areas where GPS is not received, such as department stores, museums, conference halls, schools, and tunnels, which are indoor public places. Accordingly, research on the recent indoor positioning technology based on light detection and ranging (LiDAR) equipment is increasing to build a landmark database. Focusing on the accessibility of building a landmark database, this study attempted to develop a technique for estimating the user's location by using a single image taken of a landmark based on a mobile device and the landmark database information constructed in advance. First, a landmark database was constructed. In order to estimate the user's location only with the mobile image photographing the landmark, it is essential to detect the landmark from the mobile image, and to acquire the ground coordinates of the points with fixed characteristics from the detected landmark. In the second step, by applying the bag of words (BoW) image search technology, the landmark photographed by the mobile image among the landmark database was searched up to a similar 4th place. In the third step, one of the four candidate landmarks searched through the scale invariant feature transform (SIFT) feature point extraction technique and Homography random sample consensus(RANSAC) was selected, and at this time, filtering was performed once more based on the number of matching points through threshold setting. In the fourth step, the landmark image was projected onto the mobile image through the Homography matrix between the corresponding landmark and the mobile image to detect the area of the landmark and the corner. Finally, the user's location was estimated through the location estimation technique. As a result of analyzing the performance of the technology, the landmark search performance was measured to be about 86%. As a result of comparing the location estimation result with the user's actual ground coordinate, it was confirmed that it had a horizontal location accuracy of about 0.56 m, and it was confirmed that the user's location could be estimated with a mobile image by constructing a landmark database without separate expensive equipment.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.3
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• pp.283-290
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• 2016

Even though existing methods for orthophoto production in traditional photogrammetry are effective in large areas, they are inefficient when dealing with change detection of geometric features and image production for short time periods in small areas. In recent years, the UAV (Unmanned Aerial Vehicle), equipped with various sensors, is rapidly developing and has been implemented in various ways throughout the geospatial information field. The data and imagery of specific areas can be quickly acquired by UAVs at low costs and with frequent updates. Furthermore, the redundancy of geospatial information data can be minimized in the UAV-based orthophoto generation. In this paper, the orthophoto and DEM (Digital Elevation Model) are generated using a standard low-end UAV in small sloped areas which have a rather low accuracy compared to flat areas. The RMSE of the check points is σ_H = ±0.12 m on a horizontal plane and σ_V = ±0.09 m on a vertical plane. As a result, the maximum and mean RMSE are in accordance with the working rule agreement for the airborne laser scanning surveying of the NGII (National Geographic Information Institute) on a 1/500 scale digital map. Through this study, we verify the possibilities of the orthophoto generation in small slope areas using general-purpose low specification UAV rather than a high cost surveying UAV.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.8
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• pp.215-224
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• 2013

An efficient homography estimation method for large sized images is proposed. Estimating an accurate homography is one of the most important parts in image stitching processes. Since hardwares have been advanced, it has been passible to take higher resolution images. However, computational cost for estimating homography has been also increased. Specifically, when too many features exist in the images, it requires lots of computations to estimate a correct homography. Furthermore, there is a high probability of obtaining an incorrect homography. Therefore, we propose a numerical method to extract the appropriate correspondences from several down-scaled images to estimate and compensate the homography numerically for restoring an original homography. Also, if there is an unbalance in color tone between the reference and the target images, we make them balanced by using local information of the overlapped regions. Experimental results show that proposed method is three times faster in 3.2 mega pixel images, five times faster in 8mega pixel images than the conventional approach. Therefore, we believe that the proposed method can be a useful tool to efficiently estimate a homography.

• Journal of Conservation Science
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• v.25 no.3
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• pp.255-271
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• 2009

This study was examined interpretation of making techniques and provenance interpretation of raw materials for the potteries from the Nongseori site in Giheung based on archaeometric characteristics. The potteries are classified into three groups according to the archaeological age. The texture of Neolithic age potteries is sandy soil added a lot of temper such as talc and mica, and Bronze age potteries contain sandy materials which occur naturally include quartz, orthoclase, plagioclase and mica. On the other hand, Proto-three Kingdom Age potteries made of silty soil that sift out coarse minerals from the clay. But all pottery and soil samples in the study were very similar patterns with geochemical evolution trend. This result is sufficient evidence that all pottery samples were produced using the same raw materials from the host rocks around of the site area. The Neolithic age potteries had loose texture and fired probably about 700 to $760^{\circ}C$. The Bronze age potteries had experienced firing about 850 to $900^{\circ}C$. And Proto-three Kingdom Age potteries had compact textured and fired from 900 to $1,050^{\circ}C$. The making techniques of potteries are not represented discontinuation characteristics about the periodic time sequences, and are suggested that revealed a transitional change patterns for production techniques.

• Journal of Korean Society for Geospatial Information Science
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• v.23 no.1
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• pp.129-135
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• 2015

The Ubiquitous City (U-City) spatial information technology aimed to provide services freely anytime and anywhere by converging high-tech information & communication technology in urban infrastructure has been available in diverse patterns. In particular, there have been studies on the development of 3D spatial information after selecting and matching key points with stereo images from the many Closed Circuit TV (CCTV) in the U-City. However, the data mostly used in extracting matching points haven't considered external environmental impacts such as illuminance. This study tested how much the matching points needed to construct 3D spatial information with the CCTV whose image quality is dependent upon changes in illuminance fluctuate under the same hardware performances. According to analysis on the number of matching points by illuminance, the number of matching points increased up to 3,000Lux in proportion to the illuminance when IRIS, shutter speed and ISO were fixed. In addition, a border between an object and background became more distinctive. When there was too much light, however, the page became brighter, and noise occurred. Furthermore, it was difficult to name key points because of the collapse of an inter-object border. It appears that if filmed with the study results, the number of matching points would increase.

• Korean Journal of Poultry Science
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• v.43 no.4
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• pp.263-272
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• 2016

In this study, we aimed to identify the nonsynonymous single nucleotide polymorphisms (nsSNPs) located in lipid metabolism-related genes because lipids are an important factor affecting the taste and flavor of meat, and they predict the functional consequences. The results showed that we identified 139 common nsSNPs in all five Korean native chicken (KNC) lines from the 81 genes related to lipid metabolism. Furthermore, sorting intolerant from tolerant (SIFT) and polymorphism phenotyping v2 (Polyphen-2) analyses predicted that among the genes, 14 nsSNPs of nine genes might be deleterious. Protein domain prediction of the nine genes revealed that all deleterious nsSNPs identified in this study were located outside the functional domain. This observation suggests that the common deleterious nsSNPs might be dispensable and have a minor effect on the traits of the KNCs.

• Journal of Biomedical Engineering Research
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• v.32 no.3
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• pp.237-244
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• 2011

In this paper, a feature-based registration technique is proposed for pre-contrast and post-contrast lung CT images. It utilizes three dimensional(3-D) features with their descriptors and estimates feature correspondences by nearest neighborhood matching in the feature space. We design a transformation model between the input image pairs using a free form deformation(FFD) which is based on B-splines. Registration is achieved by minimizing an energy function incorporating the smoothness of FFD and the correspondence information through a non-linear gradient conjugate method. To deal with outliers in feature matching, our energy model integrates a robust estimator which discards outliers effectively by iteratively reducing a radius of confidence in the minimization process. Performance evaluation was carried out in terms of accuracy and efficiency using seven pairs of lung CT images of clinical practice. For a quantitative assessment, a radiologist specialized in thorax manually placed landmarks on each CT image pair. In comparative evaluation to a conventional feature-based registration method, our algorithm showed improved performances in both accuracy and efficiency.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.4
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• pp.234-252
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• 2020

This paper is to verify the effectiveness of 'Hybrid Disaster Management Strategy' that integrates 'RTM(Real-time Monitoring) based On-line' and 'UAV based Off-line' system. For landslide prone area where sensors were installed, the conventional way of risk management so far has entirely relied on RTM data collected from the field through the instrumentation devices. But it's not enough due to the limitation of'Pin-point sensor'which tend to provide with only the localized information where sensors have stayed fixed. It lacks, therefore, the whole picture to be grasped. In this paper, utilizing 'Digital Photogrammetry Software Pix4D', the possibility of inference for the deformation of ungauged area has been reviewed. For this purpose, actual measurement data from RTM were compared with the estimated value from 3D point cloud outcome by UAV, and the consequent results has shown very accurate in terms of RMSE.

• Journal of the Korea institute for structural maintenance and inspection
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• v.26 no.6
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• pp.157-166
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• 2022

Structural supervision on the construction site has been performed based on visual inspection, which is highly labor-intensive and subjective. In this study, the remote technique was developed to improve the efficiency of the measurements on rebar spacing using a 360° camera and reconstructed 3D models. The proposed method was verified by measuring the spacings in reinforced concrete structure, where the twelve locations in the construction site (265 m²) were scanned within 20 seconds per location and a total of 15 minutes was taken. SLAM, consisting of SIFT, RANSAC, and General framework graph optimization algorithms, produces RGB-based 3D and 3D point cloud models, respectively. The minimum resolution of the 3D point cloud was 0.1mm while that of the RGB-based 3D model was 10 mm. Based on the results from both 3D models, the measurement error was from 10.8% to 0.3% in the 3D point cloud and from 28.4% to 3.1% in the RGB-based 3D model. The results demonstrate that the proposed method has great potential for remote structural supervision with respect to its accuracy and objectivity.