• The Transactions of the Korea Information Processing Society
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• v.5 no.7
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• pp.1923-1932
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• 1998

This paper deals with a 2-D objects recognition algorithm. And in this paper, we present an algorithm which can reduce the computation time in model retrieval by means of hashing technique instead of using the binary~tree method. In this paper, we treat an object boundary as a string of structural units and use an attributed string matching algorithm to compute similarity measure between two strings. We select from the privileged strings a privileged string wIth mmimal eccentricity. This privileged string is treated as the reference string. And thell we wllstructed hash table using the distance between privileged string and the reference string as a key value. Once the database of all model strings is built, the recognition proceeds by segmenting the scene into a polygonal approximation. The distance between privileged string extracted from the scene and the reference string is used for model hypothesis rerieval from the table. As a result of the computer simulation, the proposed method can recognize objects only computing, the distance 2-3tiems, while previous method should compute the distance 8-10 times for model retrieval.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.45 no.9
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• pp.794-806
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• 2017

It is essential to protect the national space assets and space environment safely as a space development country from the continuously increasing space debris. And Active Debris Removal(ADR) is the most active way to solve this problem. In this paper, we studied the Artificial Neural Network(ANN) for a stable recognition model of vision-based space debris tracking system. We obtained the simulated image of the space environment by the KARICAT which is the ground-based space debris clearing satellite testbed developed by the Korea Aerospace Research Institute, and created the vector which encodes structure and color-based features of each object after image segmentation by depth discontinuity. The Feature Vector consists of 3D surface area, principle vector of point cloud, 2D shape and color information. We designed artificial neural network model based on the separated Feature Vector. In order to improve the performance of the artificial neural network, the model is divided according to the categories of the input feature vectors, and the ensemble technique is applied to each model. As a result, we confirmed the performance improvement of recognition model by ensemble technique.

• Anatomy and Cell Biology
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• v.56 no.4
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• pp.494-507
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• 2023

Vascular dementia (VaD) is characterized by progressive memory impairment, which is associated with microglia-mediated neuroinflammation. Polyphenol-rich natural plants, which possess anti-inflammatory activities, have attracted scientific interest worldwide. This study investigated whether Rubus fruticosus leaf extract (RFLE) can attenuate VaD. Sprague-Dawley rats were separated into five groups: SO, sham-operated and treated with vehicle; OP, operated and treated with vehicle; RFLE-L, operated and treated with low dose (30 mg/kg) of RFLE; RFLE-M, operated and treated with medium dose (60 mg/kg) of RFLE; and RFLE-H, operated and treated with high dose (90 mg/kg) of RFLE. Bilateral common carotid artery and hypotension were used as a modeling procedure, and the RFLE were intraorally administered for 5 days (preoperative 2 and postoperative 3 days). The rats then underwent memory tests including the novel object recognition, Y-maze, Barnes maze, and passive avoidance tests, and neuronal viability and neuroinflammation were quantified in their hippocampi. The results showed that the OP group exhibited VaD-associated memory deficits, neuronal death, and microglial activation in hippocampi, while the RFLE-treated groups showed significant attenuation in all above parameters. Next, using BV-2 microglial cells challenged with lipopolysaccharide (LPS), we evaluated the effects of RFLE in dynamics of proinflammatory mediators and the upstream signaling pathway. RFLE pretreatment significantly inhibited the LPS-induced release of nitric oxide, TNF-α, and IL-6 and upregulation of the MAPKs/NF-κB/iNOS pathway. Collectively, we suggest that RFLE can attenuate the histologic alterations and memory deficits accompanied by VaD, and these roles are, partly due to the attenuation of microglial activation.

• Journal of Broadcast Engineering
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• v.19 no.5
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• pp.640-655
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• 2014

Many of today's video systems have additional depth camera to provide extra features such as 3D support. Thanks to these changes made in multimedia system, it is now much easier to obtain depth information of the video. Depth information can be used in various areas such as object classification, background area recognition, and so on. With depth information, we can achieve even higher coding efficiency compared to only using conventional method. Thus, in this paper, we propose the 2D video coding algorithm which uses depth information on top of the next generation 2D video codec HEVC. Background area can be recognized with depth information and by performing HEVC with it, coding complexity can be reduced. If current CU is background area, we propose the following three methods, 1) Earlier stop split structure of CU with PU SKIP mode, 2) Limiting split structure of CU with CU information in temporal position, 3) Limiting the range of motion searching. We implement our proposal using HEVC HM 12.0 reference software. With these methods results shows that encoding complexity is reduced more than 40% with only 0.5% BD-Bitrate loss. Especially, in case of video acquired through the Kinect developed by Microsoft Corp., encoding complexity is reduced by max 53% without a loss of quality. So, it is expected that these techniques can apply real-time online communication, mobile or handheld video service and so on.

• Journal of Aerospace System Engineering
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• v.15 no.1
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• pp.102-110
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• 2021

Recently, multi-copters equipped with various collision avoidance sensors have been introduced to improve flight stability. LiDAR is used to recognize a three-dimensional position. Multiple cameras and real-time SLAM technology are also used to calculate the relative position to obstacles. A three-dimensional depth sensor with a small process and camera is also used. In this study, a small collision-avoidance multi-copter system capable of in-door flight was developed as a platform for the development of collision avoidance software technology. The multi-copter system was equipped with LiDAR, 3D depth sensor, and small image processing board. Object recognition and collision avoidance functions based on the YOLO algorithm were verified through flight tests. This paper deals with recent trends in drone collision avoidance technology, system design/manufacturing process, and flight test results.

• Journal of KIISE:Computing Practices and Letters
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• v.8 no.5
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• pp.562-573
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• 2002

In this paper, we propose a method for measuring the volume of packages for the efficient handling of the packages. Using the geometrical characteristics of the rectangular parallelepiped type objects, the method measures the volume of packages with one camera only in real time. In preprocessing of volume measurement, the method extracts outer lines of the object and then crossing points of the lines as feature points or vertexes. From these cross points(-feature points-), the volume of the package is calculated. Compared to the direct feature extraction, the proposed method shows especially the blurring robust result by using the line for feature extraction. Additionally, the method can get the stable result by considering object's direction. From experimental results, it is demonstrated that this method is very effective for the real time volume measurement of the rectangular parallelepiped.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.877-881
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• 2008

In this paper, we propose a real-time people tracking system with multiple CCD cameras for security inside the building. The camera is mounted from the ceiling of the laboratory so that the image data of the passing people are fully overlapped. The implemented system recognizes people movement along various directions. To track people even when their images are partially overlapped, the proposed system estimates and tracks a bounding box enclosing each person in the tracking region. The approximated convex hull of each individual in the tracking area is obtained to provide more accurate tracking information. To achieve this goal, we propose a method for 3D walking human tracking based on the IMPRESARIO framework incorporating cascaded classifiers into hypothesis evaluation. The efficiency of adaptive selection of cascaded classifiers have been also presented. We have shown the improvement of reliability for likelihood calculation by using cascaded classifiers. Experimental results show that the proposed method can smoothly and effectively detect and track walking humans through environments such as dense forests.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.45 no.6
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• pp.49-59
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• 2008

SIFT(Scale Invariant Feature Transform) is an algorithm to extract vectors at pixels around keypoints, in which the pixel colors are very different from neighbors, such as vortices and edges of an object. The SIFT algorithm is being actively researched for various image processing applications including 3-D image constructions, and its most computation-intensive stage is a keypoint localization. In this paper, we develope a fixed-point model of the keypoint localization and propose its efficient hardware architecture for embedded applications. The bit-length of key variables are determined based on two performance measures: localization accuracy and error rate. Comparing with the original algorithm (implemented in Matlab), the accuracy and error rate of the proposed fixed point model are 93.57% and 2.72% respectively. In addition, we found that most of missing keypoints appeared at the edges of an object which are not very important in the case of keypoints matching. We estimate that the hardware implementation will give processing speed of $10{\sim}15\;frame/sec$, while its fixed point implementation on Pentium Core2Duo (2.13 GHz) and ARM9 (400 MHz) takes 10 seconds and one hour each to process a frame.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.2
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• pp.91-108
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• 2022

In most cases, optical images have been used as training data of DL (Deep Learning) models for object detection, recognition, identification, classification, semantic segmentation, and instance segmentation. However, properties of 3D objects in the real-world could not be fully explored with 2D images. One of the major sources of the 3D geospatial information is DSM (Digital Surface Model). In this matter, characteristic information derived from DSM would be effective to analyze 3D terrain features. Especially, man-made objects such as buildings having geometrically unique shape could be described by geometric elements that are obtained from 3D geospatial data. The background and motivation of this paper were drawn from concept of the intrinsic image that is involved in high-level visual information processing. This paper aims to extract buildings after classifying terrain features by training DL model with DSM-derived information including slope, aspect, and SRI (Shaded Relief Image). The experiments were carried out using DSM and label dataset provided by ISPRS (International Society for Photogrammetry and Remote Sensing) for CNN-based SegNet model. In particular, experiments focus on combining multi-source information to improve training performance and synergistic effect of the DL model. The results demonstrate that buildings were effectively classified and extracted by the proposed approach.

• Journal of the Institute of Convergence Signal Processing
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• v.19 no.4
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• pp.180-185
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• 2018

We have developed an interactive signage system based on floating hologram by combining hologram technology and ICT technology, which can be competitive to small businesses that have excellent products and services. The developed interactive signage system can be used for publicity and marketing of small business owners at low cost, introducing menus with 3D hologram images, and providing various contents responding to user's hand movements. The developed system is able to detect 10 finger movements at a rate of 290 frames per second in a range of 60cm and a range of 150 degrees. We also confirmed that the virtual touch function operates normally by dividing the user's motion recognition into the hover zone and the touch zone by the physical motion experiment of the leap motion object.