• Journal of Korean Society for Geospatial Information Science
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• v.10 no.3 s.21
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• pp.79-87
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• 2002

This paper proposes an approach of automatically identifying the center of fiducial marks using radiometric and geometric characteristics of those marks existing on aerial photographs. Candidate region surrounding a mark, based on radiometric strategy, is determined by producing a bi-level image and by applying morphological operations. Based on geometric strategy, the central location of a mark is determined by applying ${\bigtriangledown}^G$ filtering and symmetry-enhancement filtering, and by finding peak location of symmetry. Evaluation with respect to 66 cases of sub-images containing a fiducial mark showed that the central location of the mark is determined up to around one pixel difference whit it is compared to a manual inspection.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.556-557
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• 2018

About 350 shelters nationwide go through about 100,000 organic animals every year. If you are not adopted by the adoption candidate, you will be euthanized in just one out of every fourteen days after entering the shelter. Therefore, in order to prevent the occurrence of organic animals, it is necessary to register the companion animal easily and to register the inscription to manage the history. In this paper, we propose a local technician who can describe feature points in inscription images to develop recognition technology through inscription, which can distinguish companion animals such as human fingerprints.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.8B
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• pp.1391-1399
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• 2000

In this paper, we discussed the region-based image retrieval method using image segmentation. We proposed a segmentation method which can reduce the effect of a irregular light sources. The image segmentation method uses a region-merging, and candidate regions which are merged were selected by the energy values of high frequency bands in discrete wavelet transform. The content-based image retrieval is executed by using the segmented region information, and the images are retrieved by a color, texture, shape feature vector. The similarity measure between regions is processed by the Euclidean distance of the feature vectors. The simulation results shows that the proposed method is reasonable.

• The Bulletin of The Korean Astronomical Society
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• v.36 no.1
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• pp.87.2-87.2
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• 2011

We report our 110 ks Chandra observations of the supernova remnant (SNR) 0104-72.3 in the Small Magellanic Cloud (SMC). The X-ray morphology shows two prominent lobes along the northwest-southeast direction and a soft faint arc in the east. Previous low resolution X-ray images attributed the unresolved emission from the southeastern lobe to a Be/X-ray star. Our high resolution Chandra data clearly shows that this emission is diffuse, shock-heated plasma, with negligible X-ray emission from the Be star. The eastern arc is positionally coincident with a filament seen in optical and infrared observations. Its X-ray spectrum is well fit by plasma of normal SMC abundances, suggesting that it is from shocked ambient gas. The X-ray spectra of the lobes show overabundant Fe, which is interpreted as emission from the reverse-shocked Fe-rich ejecta. The overall spectral characteristics of the lobes and the arc are similar to those of Type Ia SNRs, and we propose that SNR 0104-72.3 is the first case for a robust candidate Type Ia SNR in the SMC. On the other hand, the remnant appears to be interacting with dense clouds toward the east and to be associated with a nearby star-forming region. These features are unusual for a standard Type Ia SNR. Our results suggest an intriguing possibility that the progenitor of SNR 0104-72.3 might have been a white dwarf of a relatively young population.

• Genomics & Informatics
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• v.4 no.2
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• pp.77-79
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• 2006

In order to identify novel proapoptotic genes, we screened approximately 1,000 hypothetical genes whose functions are completely unknown. After these genes were transiently expressed in HeLa cells, their nuclei images were captured using automated high-speed fluorescence microscope, through which the ratio of apoptotic nuclei was estimated. We selected genes that induce greater than 3-fold increase in apoptotic nuclei compared to that of the vector control. The candidate proapoptotic genes were sequenced and their effects on cell death were further confirmed by the additional assay, DNA fragmentation ELISA. Finally, we were able to identify 4 full-length hypo-thetical genes with proapoptotic activity.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.193-196
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• 2010

In this paper, we propose a method to classify the types of vehicle as full, medium, or small size. The proposed method is composed of three steps. First, after obtaining vehicle contour from template candidate image, edge distance template is created by distance transform of the vehicle's contour. Second, the vehicle type of input image is classified as the type of template which has minimal edge distance with input image. The edge distance value means the measurement of distance between input image and template at each pixel which is part of vehicle contour. Experimental results demonstrate that our method presented a good performance of 80% about test images.

• Journal of the Institute of Convergence Signal Processing
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• v.12 no.1
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• pp.33-37
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• 2011

This paper presents the frequency spectral analysis based on FFT of the infrared ray fire thermal image, it is an object to deduce the conditions for determining fire alarm through the image processing with the frequency domain. After the candidate regions are separated by using pre-defined brightness value, the fast fourier transform is performed for consecutive infrared thermal images, the frequency spectral analysis of the thermal image analyzed DC and AC frequency distribution. The fire criterion of the thermal image was presented based on the analyzed result and a practicality was confirmed through the computer simulation.

• Proceedings of the Korean Information Science Society Conference
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• 2010.06c
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• pp.447-451
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• 2010

In this paper, we propose a simple but effective algorithm to increase the speed of Emphysema region classification. Emphysema region classification method based on CT image consumes a lot of time because of the large number of subregions due to the large size of CT image. Some of the sub-regions contain no Emphysema and the classification of these regions is worthless. To speed up the classification process, we create an algorithm to select Emphysema region candidates and only use these candidates in the Emphysema region classification instead of all of the sub-regions. First, the lung region is detected. Then we threshold the lung region and only select the dark pixels because Emphysema only appeared in the dark area of the CT image. Then the thresholded pixels are clustered into a region that called the Emphysema pre-detected region or Emphysema region candidate. This region is then divided into sub-region for the Emphysema region classification. The experimental result shows that Emphysema region classification using predetected Emphysema region decreases the size of lung region which will result in about 84.51% of time reduction in Emphysema region classification.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.1
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• pp.95-101
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• 2007

Recently, two phase scheme for removing impulse noise in images is proposed. This algorithms first detect the noise candidates based on the adaptive median filter, and then apply optimizing techniques recursively only to those noise candidates to restore image. Thus the noise detector with high accuracy is important role on this algorithm, In this paper, novel noise detector is proposed, which can detect impose noise with high accuracy while reducing the probability of false detecting image details as impulses. And the method for reducing computational cost of regularization phase is presented also.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.5
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• pp.331-341
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• 2019

With the popularity of sensor-rich environments, smartphones have become one of the major platforms for obtaining and sharing information. Since it is difficult to utilize GNSS (Global Navigation Satellite System) inside the area with many buildings, the localization of smartphone in this case is considered as a challenging task. To resolve problem of localization using smartphone a four step image-based localization method and procedure is proposed. To improve the localization accuracy of smartphone datasets, MMS (Mobile Mapping System) and Google Street View were utilized. In our approach first, the searching for candidate matching image is performed by the query image of smartphone's using GNSS observation. Second, the SURF (Speed-Up Robust Features) image matching between the smartphone image and reference dataset is done and the wrong matching points are eliminated. Third, the geometric transformation is performed using the matching points with 2D affine transformation. Finally, the smartphone location and attitude estimation are done by PnP (Perspective-n-Point) algorithm. The location of smartphone GNSS observation is improved from the original 10.204m to a mean error of 3.575m. The attitude estimation is lower than 25 degrees from the 92.4% of the adjsuted images with an average of 5.1973 degrees.