• Journal of Korea Multimedia Society
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• v.7 no.12
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• pp.1657-1664
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• 2004

We propose a method that classifies images into two object types man-made and natural objects. A central object is extracted from each image by using central object extraction method[1] before classification. A central object in an images defined as a set of regions that lies around center of the image and has significant color distribution against its surrounding. We define three measures to classify the object images. The first measure is energy of edge direction histogram. The energy is calculated based on the direction of only non-circular edges. The second measure is an energy difference along directions in Gabor filter dictionary. Maximum and minimum energy along directions in Gabor filter dictionary are selected and the energy difference is computed as the ratio of the maximum to the minimum value. The last one is a shape of an object, which is also represented by Gabor filter dictionary. Gabor filter dictionary for the shape of an object differs from the one for the texture in an object in which the former is computed from a binarized object image. Each measure is combined by using majority rule tin which decisions are made by the majority. A test with 600 images shows a classification accuracy of 86%.

• The korean journal of orthodontics
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• v.28 no.4 s.69
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• pp.669-679
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• 1998

During diagnostic process of the orthodontic patients, it is not unusual to find canine impaction. Generally, the chief complaint of the patients is crowding or antetior crossbite which is not related with canine impaction, but sometimes they complainted delayed eruption of the canine or deviation of the adjacent teeth caused by canine impaction. Orthodondists have to make the proper treatment plan according to final treatment goals. On the following cases, two patients were diagnosed as a malocclusion with canine impaction, and were treated by different accesses, one by extraction, and the other by non-extraction each.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.51 no.11
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• pp.544-550
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• 2002

This paper describes a strategy of a daily optimal operational scheduling on the industrial cogeneration system. The cogeneration system selected to establish the scheduling consists of three units and several auxiliary devices which include three auxiliary boilers, t재 waste boilers and three sludge incinerators. One unit generated electrical and thermal energy using the back pressure turbine. The other two units generate the energy using the extraction condensing turbine. Three auxiliary devices operate to supply energy to the loads with three units. The cogeneration system is able to supply enough the thermal energy to the thermal load, however it can not sufficiently supply the electric energy to the electrical load. Therefore the insufficient electric energy is compensated by buying electrical energy from utility. In this paper, the evolutionary algorithms was applied to establish the optimal scheduling for the cogeneration systems. Also the GUI System was developed using established mathematics medeling and evolutionary algorithms in order that non-experts are able to establish operational scheduling. This results revel that the proposed modeling and strategy can be effectively applied to cogeneration system for paper mill.

• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.1236-1239
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• 2002

When we see an object, we usually can say what it is easily even for the case where the object isn't shown in the frontal view. However, it is difficult to believe that all views of every object we have ever seen are fully memorized in our brain. Possibly, when an object is shown, we have some typical views of the object in our brain through our past experience and reconstruct the view to recognize what the presented object is. Non-negative Matrix Factorization (NMF) is one of the methods to extract the basis images from sample data set. The prominent feature of this method is that the reconstructed image is obtained by only additions of the basis images with suitable positive weights. So NMF can be seen more biologically plausible method than any other feature extraction methods such as Vector Quantization (VQ) and principal Component Analysis (PCA). In this paper, we adopt NMF to extract the aspect features from the set of images, which consists of various views of a given object. Some experiments are shown how much well NMF can extract the aspect features than any other methods such as VQ and PCA.

• Journal of Ginseng Research
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• v.36 no.3
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• pp.308-313
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• 2012

Fresh (raw roots), white (dried), and red (steamed-drid) ginseng samples were gamma-irradiated at 0 to 7 kGy. Electron spin resonance (ESR) technique was used to characterize the irradiation status of the samples, targeting the radiation-induced cellulose radicals after different sample pretreatments. All non-irradiated samples exhibited a single central signal (g=2.006), whose intensity showed significant increase upon irradiation. The ESR spectra from the radiation-induced cellulose radicals, with two side peaks (g=2.0201 and g=1.9851) equally spaced (${\pm}3mT$) from the central signal, were also observed in the irradiated samples. The core sample analyzed after alcoholic-extraction produced the best results for irradiated fresh ginseng samples. In the case of irradiated white and red ginseng samples, the central (natural) and radiation-induced (two-side peaks corresponding to cellulose radical) signal intensities showed little improvement on alcoholic-extraction. The water-washing step minimized the effect of $Mn^{2+}$, but reduced the intensity of side peaks making them difficult to indentify. The effect of different origins was negligible, however harvesting year showed a clear effect on radiation-induced ESR signals.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.637-641
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• 2007

Airborne LIDAR (Light Detection and Ranging) technology has reached a degree of the required accuracy in mapping professions, and advanced LIDAR systems are becoming increasingly common in the various fields of application. LiDAR data constitute an excellent source of information for reconstructing the Earth's surface due to capability of rapid and dense 3D spatial data acquisition with high accuracy. However, organizing the LIDAR data and extracting information from the data are difficult tasks because LIDAR data are composed of randomly distributed point clouds and do not provide sufficient semantic information. The main reason for this difficulty in processing LIDAR data is that the data provide only irregularly spaced point coordinates without topological and relational information among the points. This study introduces an efficient and robust method for automatic extraction of building footprints using airborne LIDAR data. The proposed method separates ground and non-ground data based on the histogram analysis and then rearranges the building boundary points using convex hull algorithm to extract building footprints. The method was implemented to LIDAR data of the heavily built-up area. Experimental results showed the feasibility and efficiency of the proposed method for automatic producing building layers of the large scale digital maps and 3D building reconstruction.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2003.04a
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• pp.471-477
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• 2003

This paper presents an algorithm that automatically extracts buildings among many different features on the earth surface by fusing LIDAR data with panchromatic aerial images. The proposed algorithm consists of three stages such as point level process, polygon level process, parameter space level process. At the first stage, we eliminate gross errors and apply a local maxima filter to detect building candidate points from the raw laser scanning data. After then, a grouping procedure is performed for segmenting raw LIDAR data and the segmented LIDAR data is polygonized by the encasing polygon algorithm developed in the research. At the second stage, we eliminate non-building polygons using several constraints such as area and circularity. At the last stage, all the polygons generated at the second stage are projected onto the aerial stereo images through collinearity condition equations. Finally, we fuse the projected encasing polygons with edges detected by image processing for refining the building segments. The experimental results showed that the RMSEs of building corners in X, Y and Z were ${\pm}$8.1cm, ${\pm}$24.7cm, ${\pm}$35.9cm, respectively.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.2
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• pp.550-555
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• 2008

An efficient production method of spirulina extract was developed by enzymatic treatment using proteolytic enzymes. The suitable dosage of Tunicase, a cell lytic enzyme, was used to be 2.0% (w/w). To maximize solid recovery and spirulina extraction (SE) index, which indicates nucleic acid-related substances content, the dosage of Alcalase, commercially available pretense, was found to be 1.0% (w/w). By simultaneous treatments using optimal dosages of Tunicase and Alcalase, the highest SE index and solid recovery were obtained. The SE index and solid recovery of simultaneous treatments were notably enhanced by 100% ($11.4%\;{\rightarrow}\;22.8%$) and 56% ($45.2%\;{\rightarrow}\;70.7%$), respectively, than those of the non-treated extracts.

• Journal of Broadcast Engineering
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• v.5 no.1
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• pp.31-40
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• 2000

In this paper, we propose an edge histogram to efficiently represent the edge distribution in the image for MPEG-7. To this end, we adopt global, semi-global, and local edge histogram bins. Also, we extract the edge information from the image in terms of image blocks rather than pixels, which reduces the extraction complexity and is also applicable to the block-based compression standards such as MPEG-1, and 2. Experimental results show that the proposed method yields better retrieval accuracy and feature extraction speed comparing to other non-homogeneous texture descriptors of MPEG-7 including the wavelet-based descriptor and local edge-based descriptor.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.77-80
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• 2013

SURF algorithm is an algorithm to extract feature points and to generate descriptors from input images. It is robust to change of environment such as scale, rotation, illumination and view points. Because of these features, it is used for many image processing applications such as object recognition, constructing panorama pictures and 3D image restoration. But there is disadvantage for real time operation because many recognition algorithms such as SURF algorithm requires a lot of calculations. In this paper, we propose a design of feature extractor and descriptor generator based on SURF for high memory efficiency. The proposed design reduced a memory access and memory usage to operate in real time.