• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.4_1
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• pp.319-326
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• 2014

The accurate geo-referencing processes that apply ground control points is prerequisite for effective end use of HRSI (High-resolution satellite imagery). Since the conventional control point acquisition by human operator takes long time, demands for the automated matching to existing reference data has been increasing its popularity. Among many options of reference data, the airborne LiDAR (Light Detection And Ranging) data shows high potential due to its high spatial resolution and vertical accuracy. Additionally, it is in the form of 3-dimensional point cloud free from the relief displacement. Recently, a new matching method between LiDAR data and HRSI was proposed that is based on the image projection of whole LiDAR data into HRSI domain, however, importing and processing the large amount of LiDAR data considered as time-consuming. Therefore, we wmotivated to ere propose a local LiDAR chip generation for the HRSI geo-referencing. In the procedure, a LiDAR point cloud was rasterized into an ortho image with the digital elevation model. After then, we selected local areas, which of containing meaningful amount of edge information to create LiDAR chips of small data size. We tested the LiDAR chips for fully-automated geo-referencing with Kompsat-2 and Kompsat-3 data. Finally, the experimental results showed one-pixel level of mean accuracy.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.4
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• pp.1-14
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• 2012

A river is defined as the watercourse flowing through its channel, and the mapping tasks of a river plays an important role for the research on the topographic changes in the riparian zones and the research on the monitoring of flooding in its floodplain. However, the utilization of the ground surveying technologies is not efficient for the mapping tasks of a river due to the irregular surfaces of the riparian zones and the dynamic changes of water level of a river. Recently, the spatial information data sets are widely used for the coastal mapping tasks due to the acquisition of the topographic information without human accessibility. In this research, we tried to extract a river from the RapidEye imagery by using the ISODATA(Iterative Self_Organizing Data Analysis) classification algorithm with the two different parameters(NIR (Near Infra-Red) band and NDVI(Normalized Difference Vegetation Index)). First, the two different images(the NIR band image and the NDVI image) were generated from the RapidEye imagery. Second, the ISODATA algorithm were applied to each image and each river was generated in each image through the post-processing steps. River boundaries were also extracted from each classified image using the Sobel edge detection algorithm. Ground truths determined by the experienced expert are used for the assessment of the accuracy of an each generated river. Statistical results show that the extracted river using the NIR band has higher accuracies than the extracted river using the NDVI.

• Archives of design research
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• v.15 no.1
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• pp.407-414
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• 2002

Human does information processing more efficiently using mental model at his understanding process. if We know what mental model is, we will know how to percept that. Similarly is it used visual mental model to percept visual object\ulcorner If it is true, we will analysis how man to understand. In this research, we have one experimentation to timid out that is true. So we did experimentation to know how man to understand new products by visual mental model. So we use 2700cc car's side view as stimuli. To A Subjects, we give them to see re\ulcorner size view before 120% ratio. To B Subject, we give them to see 120% ratio. After a experimentation, It is true that we make hypothesis that A Subjects percept this stimuli too long then B Subjects. Accordingly it proves human to use visual mental model to percept visual object. The result of experimentation, a testee use preliminary stimulus as basis of evaluation. It means that he use mental model as basis of evaluation of main stimulus. Accordingly development of new design can afford more strategic approach. Industrial designer who want to strategic approach can forced on high-weighted form attribute as consumer gives.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.11a
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• pp.1661-1664
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• 2013

본 연구는 만성 뇌졸중 환자 5 명을 대상으로 상지 운동(Affected hand의 주먹 쥐기/펴기운동)시 참가자의 운동의지와 운동 수행의 유무에 따라 차이가 있을 것을 가정하고, 운동 수행 및 운동의지가 존재하는 Active movement와 운동 수행을 하지만 운동의지가 없는 Passive movement, 운동 수행은 없지만 운동의지가 있는 Motor Imagery(MI)의 세가지 task에 따른 뇌파의 연결성을 비교하고자 한다. 이 때 EEG 영역 간의 연결성을 보기 위한 분석 방식 중 하나인 Phase locking value(PLV)를 통해 각 task 간의 차이를 비교 및 분석했다. 운동 수행은 동일하지만 운동의지 유무에 따른 차이는 Passive movement가 전반적으로 뇌 영역간 연결이 감소하고 Active movement가 motor task 시작 후 375ms를 기점으로 급격히 증가함을 보이는 데에서 발견할 수 있었으며, 운동 수행 유무에 따른 차이는 687.5ms 이후 Active movement에 비해 MI에서 뇌 영역 간 연결 수가 확연히 감소하는 데에서 큰 차이를 나타내었다. 이에 따라 본 연구에서는 만성 뇌졸중 환자의 상지운동 시의 motor task에 따른 EEG 영역간의 연결성을 토대로 운동의지 검출이 가능성이 있음을 밝혔다.

• Korean Journal of Remote Sensing
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• v.27 no.1
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• pp.33-41
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• 2011

In the information communication technology, it is world-widely apparent that trend movement from internet web to smartphone app by users demand and developers environment. So it needs kinds of appropriate technological responses from geo-spatial domain regarding this trend. However, most cases in the smartphone app are the map service and location recognition service, and uses of geo-spatial contents are somewhat on the limited level or on the prototype developing stage. In this study, app for extraction of corner point features using geo-spatial imagery and their linkage to database system are developed. Corner extraction is based on Harris algorithm, and all processing modules in database server, application server, and client interface composing app are designed and implemented based on open source. Extracted corner points are applied LOD(Level of Details) process to optimize on display panel. Additional useful function is provided that geo-spatial imagery can be superimposed with the digital map in the same area. It is expected that this app can be utilized to automatic establishment of POI (Point of Interests) or point-based land change detection purposes.

• The KIPS Transactions:PartB
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• v.8B no.5
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• pp.549-556
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• 2001

The general problems of recovering 3D for 2D imagery require the depth information for each picture element form focus. The manual creation of those 3D models is consuming time and cost expensive. The goal in this paper is to simplify the depth estimation algorithm that extracts the depth information of every region from monocular image sequence with camera translation to implement 3D video in realtime. The paper is based on the property that the motion of every point within image which taken from camera translation depends on the depth information. Full-search motion estimation based on block matching algorithm is exploited at first step and ten, motion vectors are compensated for the effect by camera rotation and zooming. We have introduced the algorithm that estimates motion of object by analysis of monocular motion picture and also calculates the averages of frame depth and relative depth of region to the average depth. Simulation results show that the depth of region belongs to a near object or a distant object is in accord with relative depth that human visual system recognizes.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.4
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• pp.293-300
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• 2013

Road signs are important infrastructures for safe and smooth traffic by providing useful information to drivers. It is necessary to establish road sign DB for managing road signs systematically. To provide such DB, manually detection and recognition from imagery can be done. However, it is time and cost consuming. In this study, we proposed algorithms for automatic recognition of direction information in road sign image. Also we developed algorithm code using OpenCV library, and applied it to road sign image. To automatically detect and recognize direction information, we developed program which is composed of various modules such as image enhancement, image binarization, arrow region extraction, interesting point extraction, and template image matching. As a result, we can confirm the possibility of automatic recognition of direction information in road sign image.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2017.04a
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• pp.42-42
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• 2017

Prediction of rice yield during a growing season would be very helpful to magnify rice yield as it also allows better farm practices to maximize yield with greater profit and lesser costs. UAV imagery based automatic detection of rice can be a relevant solution for early prediction of yield. So, we propose an image processing technique to predict rice yield using low altitude UAV images. We proposed $L^*a^*b^*$ color space based image segmentation algorithm. All images were captured using UAV mounted RGB camera. The proposed algorithm was developed to find out rice grain area from the image background. We took RGB image and applied filter to remove noise and converted RGB image to $L^*a^*b^*$ color space. All color information contain in both $a^*$ and $b^*$ layers and by using k-mean clustering classification of these colors were executed. Variation between two colors can be measured and labelling of pixels was completed by cluster index. Image was finally segmented using color. The proposed method showed that rice grain could be segmented and we can recognize rice grains from the UAV images. We can analyze grain areas and by estimating area and volume we could predict rice yield.

• Journal of Biosystems Engineering
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• v.36 no.6
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• pp.484-490
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• 2011

Defects exist underneath the fruit skin are not easily discernable by using conventional color imaging technique in the visible wavelength ranges. Development of sensitive detection methods for the defects is necessary to ensure accurate quality sorting of fruits. Hyperspectral imaging techniques, which combine the features of image and spectroscopy to acquire spatial and spectral information simultaneously, have demonstrated good potentials for identifying and detecting anomalies on biological substances. In this study, a high spatial resolution hyperspectral reflectance technique was presented as a tool for detecting bruises on apple. The two-band ratio (494 nm / 952 nm) and simple threshold methods were applied to investigate the feasibility of discriminating the bruises from sound tissue of apple. The pixel wise accuracy of the discrimination was 74%. The resultant images processed with selected wavebands and morphologic algorithm distinctively showed the early stages of bruises on apple which were not discernable by naked eyes as well as a conventional color camera. Results demonstrated good potential of the hyperspectral reflectance imaging for detection of bruises on apple.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.11
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• pp.1115-1121
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• 2009

For HRI (Human-Robot Interaction) in daily life, robots need to recognize non-rigid objects such as clothes and blankets. However, the recognition of non-rigid objects is challenging because of the variation of the shapes according to the places and laying manners. In this paper, the cognition of non-rigid object based on a cognitive system is presented. The characteristics of non-rigid objects are analysed in the view of HRI and referred to design a framework for the cognition of them. We adopt a linguistic cognitive system for describing all of the events happened to robots. When an event related to the non-rigid objects is occurred, the cognitive system describes the event into a sentential form and stores it at a sentential memory, and depicts the objects with a spatial model for being used as references. The cognitive system parses each sentence syntactically and semantically, in which the nouns meaning objects are connected to their models. For answering the questions of humans, sentences are retrieved by searching temporal information in the sentential memory and by spatial reasoning in a schematic imagery. Experiments show the feasibility of the cognitive system for cognizing non-rigid objects in HRI.