• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.25 no.4
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• pp.327-336
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• 2007

The 3D building modeling is one of crucial components in building 3D geospatial information. The existing methods for 3D building modeling depend mainly on manual photogrammetric processes by stereoplotter compiler, which indeed take great amount of time and efforts. In addition, some automatic methods that were proposed in research papers and experimental trials have limitations of describing the details of buildings with lack of geometric accuracy. It is essential in automatic fashion that the boundary and shape of buildings should be drawn effortlessly by a sophisticated algorithm. In recent years, airborne LiDAR data representing earth surface in 3D has been utilized in many different fields. However, it is still in technical difficulties for clean and correct boundary extraction without human intervention. The usage of airborne LiDAR data will be much feasible to reconstruct the roof tops of buildings whose boundary lines could be taken out from existing digital maps. The paper proposed a method to reconstruct the roof tops of buildings using airborne LiDAR data with building boundary lines from digital map. The primary process is to perform octree-based segmentation to airborne LiDAR data recursively in 3D space till there are no more airborne LiDAR points to be segmented. Once the octree-based segmentation has been completed, each segmented patch is thereafter merged based on geometric spatial characteristics. The experimental results showed that the proposed method were capable of extracting various building roof components such as plane, gable, polyhedric and curved surface.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.4
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• pp.403-411
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• 2014

In this paper, an algorithm of extracting the features of home appliances and automatically building a database to identify home appliances is designed and presented. For the verification, a software library supporting this algorithm is implemented and added to an power management system server, which was already implemented to support real-time monitoring of home appliances' power consumption status and controlling their power. The implemented system consists of a system server and clients, each of which measures the power consumed by a home appliance plugged in it and transmits the information to the server in real-time over a wireless network. Through experiments, it is verified that it is possible to identify any home appliance connected to a specific client.

• Journal of the Korea Society of Computer and Information
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• v.10 no.4 s.36
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• pp.203-211
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• 2005

In this paper, we propose a new automatic fingerprint identification system that identifies individuals in large databases. The algorithm consists of three steps; preprocessing, classification, and matching, in the classification. we present a new classification technique based on the statistical approach for directional image distribution. In matching, we also describe improved minutiae candidate pair extraction algorithm that is faster and more accurate than existing algorithm. In matching stage, we extract fingerprint minutiaes from its thinned image for accuracy, and introduce matching process using minutiae linking information. Introduction of linking information into the minutiae matching process is a simple but accurate way, which solves the problem of reference minutiae pair selection in comparison stage of two fingerprints quickly. This algorithm is invariant to translation and rotation of fingerprint. The proposed system was tested on 1000 fingerprint images from the semiconductor chip style scanner. Experimental results reveal false acceptance rate is decreased and genuine acceptance rate is increased than existing method.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.17 no.4
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• pp.106-115
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• 2003

In crossing stereo camera system as a security equipment system, a new algorithm for the tracking method of the moving object and the measurement method of distance of the object from cameras to moving object is proposed. The stereo input images are matched by a pixel for the moving object extraction, then the moving elements obtained from an adaptive threshold's value for an error correction and the moving object area extracted by noise eliminative algorithm. In addition to, the moving object traced by control pan/tilt of cameras using a coordinate value of the moving object, and the measurement method of distance to moving object by using special features of the crossing stereo camera system is proposed. From the experimental results, the proposed algorithm was found to be able to measure of the distance and trace for moving object in a stereo security camera system. The error rate of a distance measurement be existed within 6%. Moreover in implementation the proposed algorithm, the stereo security system, the automatic moving robot system and the stereo remote control system will be applied practical application.

• KSCI Review
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• v.14 no.1
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• pp.265-271
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• 2006

In this paper, we propose a new automatic fingerprint identification system that identifies individuals in large databases. The algorithm consists of three steps: preprocessing, classification, and matching, in the classification, we present a new classification technique based on the statistical approach for directional image distribution. In matching, we also describe improved minutiae candidate pair extraction algorithm that is faster and more accurate than existing algorithm. In matching stage, we extract fingerprint minutiaes from its thinned image for accuracy, and introduce matching process using minutiae linking information. Introduction of linking information into the minutiae matching process is a simple but accurate way, which solves the problem of reference minutiae pair selection in comparison stage of two fingerprints quickly. This algorithm is invariant to translation and rotation of fingerprint. The proposed system was tested on 1000 fingerprint images from the semiconductor chip style scanner. Experimental results reveal false acceptance rate is decreased and genuine acceptance rate is increased than existing method.

• Journal of the Korean Association of Geographic Information Studies
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• v.12 no.1
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• pp.1-11
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• 2009

Rapid visualization of flood area of downstream according to the dam effluent in flood season is very important in dam management works. Overlay zone of river bight should be removed to represent flood area efficiently based on flood stage which was modeled in river channels. This study applied drainage enforcement algorithm to visualize flood area considering river bight by coupling Coordinate Operation System for Flood control In Multi-reservoir (COSFIM) and Flood Wave routing model (FLDWAV). The drainage enforcement algorithm is a kind of interpolation which gives to advantage into hydrological process studies by removing spurious sinks of terrain in automatic drainage algorithm. This study presented mapping technique of flood area layer considering river bight in Namgang-Dam downstream, and developed system based on Arcobject component to execute this process automatically. Automatic extraction system of flood area layer could save time-consuming efficiently in flood inundation visualization work which was propelled based on large volume data. Also, flood area layer by coupling with IKONOS satellite image presented real information in flood disaster works.

• The KIPS Transactions:PartB
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• v.19B no.1
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• pp.1-8
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• 2012

Mosaic is to make a big image by gathering lots of small materials having various colors. With advance of digital imaging techniques, photomosaic techniques using photos are widely used. In this paper, we presents an automatic photomosaic algorithm based on adaptive tiling and block matching. The proposed algorithm is composed of two processes: photo database generation and photomosaic generation. Photo database is a set of photos (or tiles) used for mosaic, where a tile is divided into $4{\times}4$ regions and the average RGB value of each region is the feature of the tile. Photomosaic generation is composed of 4 steps: feature extraction, adaptive tiling, block matching, and intensity adjustment. In feature extraction, the feature of each block is calculated after the image is splitted into the preset size of blocks. In adaptive tiling, the blocks having similar similarities are merged. Then, the blocks are compared with tiles in photo database by comparing euclidean distance as a similarity measure in block matching. Finally, in intensity adjustment, the intensity of the matched tile is replaced as that of the block to increase the similarity between the tile and the block. Also, a tile redundancy minimization scheme of adjacent blocks is applied to enhance the quality of mosaic photos. In comparison with Andrea mosaic software, the proposed algorithm outperforms in quantitative and qualitative analysis.

• Journal of KIISE:Software and Applications
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• v.29 no.3
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• pp.202-210
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• 2002

During the last few years, the extraction and reconstruction of the blood vessels in the medical image has been actively researched and the analysis for the retinal vessel structure has provided important information for diagnosis and remedy of the retinopathy patients. In this research, we propose the algorithm that tracks automatically the entire retinal vessel in retinal image acquired by the ICG(IndoCyanine Green) technology. This algorithm extracts contours and centers by estimating the local maxima and processing directions and detects bifurcations and junctions by comparing direction components of the local maxima from the gradient magnitude profile of each blood vessel. We present experimental results that the entire blood vessel is automatically reconstructed and is excellent in accuracy and connectivity after applying our algorithm to the ICG retinal images of patients.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.1
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• pp.107-114
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• 2017

Iris diagnosis is an alternative medicine to diagnose the disease of the patient by using different of the iris pattern, color and other characteristics. This paper proposed a disease prediction algorithm that using the iris regions that analyze iris change to using differential image of iris image. this method utilize as patient's health examination according to iris change. Because most of previous studies only find a sign pattern in a iris image, it's not enough to be used for a iris diagnosis system. We're developed an iris diagnosis system based on a iris images processing approach, It's presents the extraction algorithms of 8 major iris signs and correction manually for improving the accuracy of analysis. As a result, PNSR of applied edge detection image is about 132, and pattern matching area recognition presented practical use possibility by automatic diagnostic that presume situation of human body by iris about 91%.

• Journal of KIISE:Software and Applications
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• v.33 no.10
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• pp.851-861
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• 2006

The paper proposes a novel unsupervised video object segmentation algorithm for image sequences with low depth-of-field (DOF), which is a popular photographic technique enabling to represent the intention of photographer by giving a clear focus only on an object-of-interest (OOI). The proposed algorithm largely consists of two modules. The first module automatically extracts OOIs from the first frame by separating sharply focused OOIs from other out-of-focused foreground or background objects. The second module tracks OOIs for the rest of the video sequence, aimed at running the system in real-time, or at least, semi-real-time. The experimental results indicate that the proposed algorithm provides an effective tool, which can be a basis of applications, such as video analysis for virtual reality, immersive video system, photo-realistic video scene generation and video indexing systems.