• Journal of the Korean Society of Systems Engineering
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• v.16 no.1
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• pp.51-57
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• 2020

The fighter pilot uses radar mounted on the fighter to obtain high-resolution SAR (Synthetic Aperture Radar) images for a specific area of distance, and then the pilot visually classifies targets within the image. However, the target configuration captured in the SAR image is relatively small in size, and distortion of that type occurs depending on the depression angle, making it difficult for pilot to classify the type of target. Also, being present with various types of clutters, there should be errors in target classification and pilots should be even worse if tasks such as navigation and situational awareness are carried out simultaneously. In this paper, the concept of operation and functional structure of radar system for fighter jets were presented to transfer the SAR image target classification task of fighter pilots to radar system, and the method of target classification with high accuracy was studied using the CNN ensemble model to archive higher classification accuracy than single CNN model.

• Journal of the Korean Society of Combustion
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• v.1 no.1
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• pp.65-73
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• 1996

Flame propagation in a four-valve spark-ignition optical engine was visualized under lean-bum conditions with A/F=18 at 2000rpm. The early flame development in a four-valve pentroof-chamber single-cylinder engine was examined with imaging of the laser-induced Mie scattered light using an image-intensified CCD camera. Flame profiles along the line-of-sight were also visualized through a quartz piston window. Two-dimensional flame structures were visualized with a Proxitronic HF-1 fast motion camera system by Mie scattering from titanium dioxide particles along a planar laser sheet generated by a copper vapor laser. The flame propagation images were subsequently analysed with an image processing programme to obtain information about the flame structure under different tumble flow conditions generated by sleeved and non-sleeved intake ports. This allowed enhancement of the flame images and calculation of the enflamed area, and the displacement of its center, as a function of the tumble flow induced by the pentroof-chamber in the vicinity of spark plug. Image processing of the early flame development quantified the correlation between flame and flow characteristics near the spark plug at the time of ignition which has been known to be one of the most important factors in cyclic combustion variations in lean-burn engines. The results were also compared with direct flame images obtained from the natural flame luminosity of the lean mixture.

• The Research Journal of the Costume Culture
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• v.22 no.4
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• pp.640-653
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• 2014

The purpose of this study was to investigate the effect of store attributes on brand equity of and brand attitude toward Korean SPA brands. Data were collected from women living in Seoul in ages from 18 to 39 with purchasing experience at Korean SPA brands. A total of 554 questionnaires were used in the statistical analysis including factor analysis and structure equation analysis. The results were as follows: For store attributes, 8 factors were extracted: product assortment, fashionability, price, quality, store environment, service, convenience in location and advertisement. Two factors, brand awareness, brand image were extracted for brand equity, and brand attitude was derived as a single dimension. Product-related store attributes such as product assortment, price, quality have positive effects on brand awareness, brand image and brand attitude. Other attribute such as store environment has positive effect on brand awareness and brand image, Attribute such as advertisement has positive effect on brand awareness and service, convenience in location have positive effect on brand attitude. Moreover, brand image and brand awareness have positive effect on brand attitude. These results indicate the product-related attributes are important factors to consider for improving brand equity and brand attitude for Korean SPA brands.

• Journal of IKEEE
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• v.18 no.4
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• pp.523-531
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• 2014

In this paper, a fast single image blind denoising algorithm is presented, where noise parameters are estimated by local statistics of an observed degraded image without a prior information about the additive noise. The estimated noise parameters are used to define the constraints on the noise detection which is coupled with the 1st-order Markov Random Field. In addition, an adaptive modified weighted Gaussian filter is introduced, where variable window sizes and weighting coefficients defined by the constraints are used to control the degree of the smoothness of the reconstructed image. The experimental results demonstrate the capability of the proposed algorithm. Please put the abstract of paper here.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.318-320
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• 2006

Inaccurate localization exposes a robot to many dangerous conditions. It could make a robot be moved to wrong direction or damaged by collision with surrounding obstacles. There are numerous approaches to self-localization, and there are different modalities as well (vision, laser range finders, ultrasonic sonars). Since sensor information is generally uncertain and contains noise, there are many researches to reduce the noise. But, the correctness is limited because most researches are based on statistical approach. The goal of our research is to measure more exact robot location by matching between built VRML 3D model and real vision image. To determine the position of mobile robot, landmark-localitzation technique has been applied. Landmarks are any detectable structure in the physical environment. Some use vertical lines, others use specially designed markers, In this paper, specially designed markers are used as landmarks. Given known focal length and a single image of three landmarks it is possible to compute the angular separation between the lines of sight of the landmarks. The image-processing and neural network pattern matching techniques are employed to recognize landmarks placed in a robot working environment. After self-localization, the 2D scene of the vision is overlaid with the VRML scene.

• Journal of Korea Multimedia Society
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• v.20 no.11
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• pp.1750-1758
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• 2017

In super-resolution, various methods with Convolutional Neural Network(CNN) have recently been proposed. CNN based methods provide much higher image quality than conventional methods. Especially, VDSR outperforms other CNN based methods in terms of image quality. However, it requires a high computational complexity which prevents real-time processing. In this paper, the method to apply a deconvolution layer to VDSR is proposed to reduce computational complexity. Compared to original VDSR, the proposed method achieves the 4.46 times speed-up and its degradation in image quality is less than -0.1 dB which is negligible.

• Proceedings of the KOSOMBE Conference
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• v.1997 no.11
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• pp.137-141
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• 1997

In this study, in order to improve visualization and enhance the ability of the surgeon to perform delicate endoscopic surgery, three dimensional endoscopic system is designed. These 3D systems have our features of stereoendoscopic image processing: real time image capture and retrieve; presentation of left and right image on a single monitor; separable processing of the left and right eye images; coding of the 3D endoscopic video. For 3D endoscopic video coding, three approaches are presented based on interlaced picture structure, side-field format structure, and simulcast technique. Experimental results and performances comparisons are presented and analyzed or these approaches. Digital video coding techniques are presented or 3D endoscopic video sequences by means of an MPEG-2 video coding.

• Proceedings of the KOSOMBE Conference
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• v.1997 no.11
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• pp.294-298
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• 1997

In the magnetic resonance imaging, the fast spin echo imaging technique is a widely used clinical imaging method, since its scanning time is much shorter than the conventional spin echo imaging and it gives the almost same image quality. However, the fast spin echo technique has two times longer imaging time or the dual echo acquisition which can obtain a spin density image and a $T_2$-weighted image simultaneously. To overcome such a drawback, this paper proposes a new fast dual echo imaging technique which can give the same quality images at the single echo imaging time. The proposed technique reduces the imaging time by overlapping most of echo train data for each image reconstruction. In order to verify its validity and usability the human head experimental results which were obtained at the 0.3T permanent MRI system are presented.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1996.06c
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• pp.834-841
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• 1996

Egg production in Korea is becoming automated with a large scale farm. Although many operations in egg production have been and cracks are regraded as a critical problem. A computer vision system was built to generate images of a single , stationary egg. This system includes a CCD camera, a frame grabber board, a personal computer (IBM PC AT 486) and an incandescent back lighting system. Image processing algorithms were developed to inspect egg shell and to sort eggs. Those values of both gray level and area of dark spots in the egg image were used as criteria to detect holes in egg and those values of both area and roundness of dark spots in the egg and those values of both area and roundness of dark spots in the egg image were used to detect cracks in egg. Fro a sample of 300 eggs. this system was able to correctly analyze an egg for the presence of a defect 97.5% of the time. The weights of eggs were found to be linear to both the projected area and the perimeter of eggs v ewed from above. Those two values were used as criteria to sort eggs. Accuracy in grading was found to be 96.7% as compared with results from weight by electronic scale.

• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.186-191
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• 1998

The first step in change detection in any SAR monitoring, including SAR interferometry, is the co-registration of the images. CCPs (Ground Control Points) for co-registration are usually detected manually, but for qualitative analyses of enormous volumes of data, some automation of the process will become necessary. An automated determination of common CCPs for the same path/row data is especially desirable. We selected the intersections of linear features as the candidates of common GCPs Very bright point targets, which are commonly used as GCPs, have the drawback of appearing and disappearing depending on the conditions of the observation. But in the case of linear features, some detailed elements may appear differently in some case, but the overall line-likeness will remain. In this study, we selected 18 common GCPs for a single-look JERS-1 SAR image of Omaezaki area in central Japan. Although the GCPs in the first image had to be selected either interactively or semi-automatically, the same GCPs in all other images were successively detected automatically using a tiny sub-image around each GCP and a dilated mask of each linear feature in the first image as the reference data.