• Transactions of the Korean Society of Mechanical Engineers B
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• v.28 no.7
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• pp.800-808
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• 2004

Wind tunnel test of an airplane model with forward swept wing was done in KARI LSWT to evaluate and measure the aerodynamic characteristics of initially designed configuration. Since the given wing planform did not fully satisfy the design requirements, local flow control devices such as vortilon, vortex generator and flow fence were used to delay separation and to enhance aerodynamic characteristics. Also decision making processes of design parameters such as vertical tail boom length, the location, size and the incidence angle of horizontal tail were discussed. The general aerodynamic characteristics of forward swept wing for various control surface deflection conditions of flap, aileron and elevator were also given.

• Korean Journal of Remote Sensing
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• v.24 no.3
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• pp.267-272
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• 2008

Tree species-specific estimates with spacebome high-resolution imagery improve estimation of forest biomass which is needed to predict the long term planning for the sustainable forest management(SFM). This paper is a contribution to develop crown distinguishing coniferous species, Pinus densiflora and Pinus koraiensis, from QuickBird imagery. The proposed feature analysis derived from shape parameters and first and second-order statistical texture features of the same test area were compared for the two species separation and delineation. As expected, initial studies have shown that both formfactor and compactness shape parameters provided the successful differentiating method between the pine species within the compartment for single crown identification from spaceborne high resolution imagery. Another result revealed that the selected texture parameters - the mean, variance, angular second moment(ASM) - in the infrared band image could produce good subset combination of texture features for representing detailed tree crown outline.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.9
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• pp.300-306
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• 2012

In this paper, we propose a vision based hand motion recognition method for an untouchable user interface of smart devices. First, an original color image is converted into a gray scaled image and its spacial resolution is reduced, taking the small memory and low computational power of smart devices into consideration. For robust recognition of hand motions through separation of horizontal and vertical motions, the horizontal principal area (HPA) and the vertical principal area (VPA) are defined respectively. From the difference images of the consecutively obtained images, the center of gravity (CoG) of the significantly changed pixels caused by hand motions is obtained, and the direction of hand motion is detected by defining the least mean squared line for the CoG in time. For verifying the feasibility of the proposed method, the experiments are carried out with a vision system.

• Journal of the Korea Society of Computer and Information
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• v.15 no.10
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• pp.49-57
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• 2010

In this thesis, We studied on hand-written character recognition, that characters entered into a digital input device and remove noise and separating character elements using preprocessing. And processed character images has done thinning and 3-level wavelet transform for making normalized image and reducing image data. The structural method among the numerical Hangul recognition methods are suitable for recognition of printed or hand-written characters because it is usefull method deal with distortion. so that method are applied to separating elements and analysing texture. The results show that recognition by analysing texture is easily distinguished with respect to consonants. But hand-written characters are tend to decreasing successful recognition rate for the difficulty of extraction process of the starting point, of interconnection of each elements, of mis-recognition from vanishing at the thinning process, and complexity of character combinations. Some characters associated with the separation process is more complicated and sometime impossible to separating elements. However, analysis texture of the proposed character recognition with the exception of the complex handwritten is aware of the character.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.4
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• pp.358-365
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• 2017

In this paper, we propose an object recognition method using image information to improve the efficiency of visual servoingfor industrial manipulators in industry. This is an image-processing method for real-time responses to an abnormal situation or to external environment change in a work object by utilizing camera-image information of an industrial manipulator. The object recognition method proposed in this paper uses the Otsu method, a thresholding technique based on separation of the V channel containing color information and the S channel, in which it is easy to separate the background from the HSV channel in order to improve the recognition rate of the existing Harris Corner algorithm. Through this study, when the work object is not placed in the correct position due to external factors or from being twisted,the position is calculated and provided to the industrial manipulator.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.3 no.1
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• pp.59-68
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• 1999

Recently, research and developmental direction of communication system is concurrent adopting voice data and face image in speaking to provide more higher recognition rate then in the case of only voice data. Therefore, we present a method of lipreading in speech image sequence by using the 3-D facial shape model. The method use a feature information of the face image such as the opening-level of lip, the movement of jaw, and the projection height of lip. At first, we adjust the 3-D face model to speeching face image sequence. Then, to get a feature information we compute variance quantity from adjusted 3-D shape model of image sequence and use the variance quality of the adjusted 3-D model as recognition parameters. We use the intensity inclination values which obtaining from the variance in 3-D feature points as the separation of recognition units from the sequential image. After then, we use discrete HMM algorithm at recognition process, depending on multiple observation sequence which considers the variance of 3-D feature point fully. As a result of recognition experiment with the 8 Korean vowels and 2 Korean consonants, we have about 80% of recognition rate for the plosives and vowels. We propose that usability with visual distinguishing factor that using feature vector because as a result of recognition experiment for recognition parameter with the 10 korean vowels, obtaining high recognition rate.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.4 s.304
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• pp.49-59
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• 2005

This paper proposed a six-color separation using additional colorants and quantitative granularity metric to reduce color difference and graininess. In the conventional method, light magenta and light cyan are used in the bright region instead of magenta and cyan. However, the hue value of liBht magenta and light cyan is different from the one of magenta and cyan in CIELAB space, so that this makes the colorimetric reproduction more or less inaccurate. To improve this inaccuracy, the proposed method uses yellow and light magenta colorants as the additional colorants. In the bright region, magenta is replaced with light magenta and yellow, while cyan is replaced with light cyan and light magenta. This selection reduces hue difference because it creates the color of similar hue to magenta and cyan. In addition, smooth image can be simultaneously obtained by the less dot visibility of additional colorants. In the middle region, magenta is replaced with light magenta and magenta, while cyan is replaced with light cyan and cyan. The use of two colorants having a different concentration makes the dot Pattern coarse. To reflect this Phenomenon, quantitative granularity metric is used. In the dark region, only magenta and cyan colorant is used as usual. Through experiments, it is shown that the proposed method improves both colorimetric and smooth tone reproductions.

• Journal of Radiopharmaceuticals and Molecular Probes
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• v.7 no.2
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• pp.119-125
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• 2021

⁸²Sr for ⁸²Rb generator was produced through the irradiation of the proton beam on the ^nat.RbCI target at the target irradiation facility installed at the end of the Rl-dedicated beamline of the 100 MeV proton linear accelerator of KOMAC (Korea Multi-purpose Accelerator Complex). The average current of the proton beam was 1.2 µA for irradiation time of 150 min. For the separation and purification of the ⁸²Sr from ^nat.RbCI irradiated, Chelex-100 resin was used. The activities of ⁸²Sr in the irradiated ^nat.RbCI target solution and after purification were 45.29 µCi and 43.4 µCi, respectively. The separation and purification yield was 95.8%. As an adsorbent to be filled in the generator for ⁸²Sr adsorption hydrous tin oxide was selected. The adsorption yield of ⁸²Sr into the generator adsorbent was > 99 %, and the total amount of ⁸²Sr adsorbed to the generator was 21.6 µCi as of the day of the ⁸²Rb elution experiment. When the elution amount was 22 mL, the maximum⁸²Rb elution yield was 93.3%, and the elution yield increased as the flow rate increased. After the eluted ⁸²Rb was filled in the correction phantom of the small PET for animals, a PET image was taken. The image scan time was set to 5 min, and the phantom PET image was successfully obtained. As results of impurity analysis on eluted ⁸²Rb using ICP-MS, ^nat.Rb stable isotopes that compete in vivo of ⁸²Rb were identified as undetected levels and were determined to be No-Carrier-Added (NCA).

• The KIPS Transactions:PartB
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• v.10B no.3
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• pp.311-320
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• 2003

The Optimal filter yielding optimal texture feature separation is a most effective technique for extracting the texture objects from multiple textures images. But, most optimal filter design approaches are restricted to the issue of supervised problems. No full-unsupervised method is based on the recognition of texture objects in image. We propose a novel approach that uses unsupervised learning schemes for efficient texture image analysis, and the band-pass feature of Gabor-filter is used for the optimal filter design. In our approach, the self-organizing neural network for multiple texture image identification is based on block-based clustering. The optimal frequency of Gabor-filter is turned to the optimal frequency of the distinct texture in frequency domain by analyzing the spatial frequency. In order to show the performance of the designed filters, after we have attempted to build a various texture images. The texture objects extraction is achieved by using the designed Gabor-filter. Our experimental results show that the performance of the system is very successful.

• Journal of KIISE:Software and Applications
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• v.31 no.2
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• pp.203-212
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• 2004

The watermarking is a method to achieve the copyright protection of multimedia contents. Among several media, the left documents show very peculiar properties: block/line/word patterning, clear separation between foreground and background areas. So algorithms specific to the text documents are required that meet those properties. This paper proposes a novel watermarking algorithm for the grayscale text document images. The algorithm inserts the watermark signals through the edge direction histograms. A concept of sub-image consistency is developed that the sub-images have similar shapes in terms of edge direction histograms. Using Korean, Chinese, and English document images, the concept is evaluated and proven to be valid over a wide range of document images. To insert watermark signals, the edge direction histogram is modified slightly. The experiments were performed on various document images and the algorithm was evaluated in terms of imperceptibility and robustness.