• JSTS:Journal of Semiconductor Technology and Science
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• v.13 no.1
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• pp.34-42
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• 2013

Human faces have been broadly studied in digital image and video processing fields. An appearance-based method, the adaptive boosting learning algorithm using integral image representations has been successfully employed for face detection, taking advantage of the feature extraction's low computational complexity. In this paper, we propose a face-detection postprocessing method that equalizes instantaneous facial regions in an efficient hardware architecture for use in real-time multimedia applications. The proposed system requires low hardware resources and exhibits robust performance in terms of the movements, zooming, and classification of faces. A series of experimental results obtained using video sequences collected under dynamic conditions are discussed.

• International Journal of Advanced Culture Technology
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• v.7 no.4
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• pp.327-333
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• 2019

Wind speed data constitute important weather information for aircrafts flying at low altitudes, such as drones. Currently, the accuracy of low altitude wind predictions is much lower than that of high-altitude wind predictions. Deep neural networks are proposed in this study as a method to improve wind speed forecast information. Deep neural networks mimic the learning process of the interactions among neurons in the brain, and it is used in various fields, such as recognition of image, sound, and texts, image and natural language processing, and pattern recognition in time-series. In this study, the deep neural network model is constructed using the wind prediction values generated by the numerical model as an input to improve the wind speed forecasts. Using the ground wind speed forecast data collected at the Boseong Meteorological Observation Tower, wind speed forecast values obtained by the numerical model are compared with those obtained by the model proposed in this study for the verification of the validity and compatibility of the proposed model.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.5
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• pp.323-330
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• 2019

Radiometric normalization with multi-temporal satellite images is essential for time series analysis and change detection. Generally, relative radiometric normalization, which is an image-based method, is performed, and histogram matching is a representative method for normalizing the non-linear properties. However, since it utilizes global statistical information only, local information is not considered at all. Thus, this paper proposes a histogram matching method considering local information. The proposed method divides histograms based on density, mean, and standard deviation of image intensities, and performs histogram matching locally on the sub-histogram. The matched histogram is then further partitioned and this process is performed again, iteratively, controlled with the wasserstein distance. Finally, the proposed method is compared to global histogram matching. The experimental results show that the proposed method is visually and quantitatively superior to the conventional method, which indicates the applicability of the proposed method to the radiometric normalization of multi-temporal images with non-linear properties.

• The Korean Journal of Nuclear Medicine
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• v.23 no.2
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• pp.195-200
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• 1989

The authors studied to evaluate the difference of the diagnostic performance between reading from digital image on the video CRT of PACS (Picture Archiving and Communication System) and from analogue image of conventional film mode. We compared interpretative accuracy of above two reading modes by having two observers read a series of liver scintigrams. Images were read once from film and a second time from video CRT of elementary PACS. The concordance rate of interpretation of the two modes was in the range from 61.0% to 93.2%. The diagnostic accuracies of digital image reading and analogue image reading were 72.9% and 74.6% respectively in one observer, and 72.9% and 76.3% in another one. No significant difference in interpretative accuracy could be found between two modes of reading.

• Journal of Biosystems Engineering
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• v.28 no.2
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• pp.157-166
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• 2003

The purpose of this study is to characterize the internal physical properties of fresh Korean ginsengs (Panax ginseng C.A. Meyer) through a magnetic resonance imaging (MRI) technique. Current external visual inspection cannot determine internal quality of ginsengs successfully. Relaxation time constants, T$_1$ and T$_2$*, were obtained from a series of MR images. Calculated Ti values were varied with different physiological states of ginseng tissues. Internal imaging information was obtained nondestructively from fresh ginsengs. One- and two-dimensional image analyses were performed. One-dimensional image analysis showed a potential of age identification of ginsengs rapidly. Internal quality of normal and abnormal ginsengs was evaluated using two-dimensional MR images. Various types of internal defects such as internal cavity and rotten spot were visualized clearly. The MRI technique had a feasibility to detect internal defects of fresh ginsengs effectively.

• Journal of Advanced Navigation Technology
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• v.5 no.2
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• pp.149-157
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• 2001

A high speed data link capability is one of the critical factors in determining the performance of the spaceborne SAR system with high resolution. It is due to the strict requirement for the real-time data transmission from a series of massive raw image data of spaceborne SAR to the ground station in a limited time of mission. In this paper, based on the data link model characterized by the spaceborne small SAR system, the high rate multi-channel data link module is designed including link storage, link processor, transmitter, and wide-angle antenna. The design results are presented with the performance analysis on the data link budget as well as the multi-mode data rate in association with the SAR imaging mode of operation from high resolution to the wide swath.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2000.11b
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• pp.279-286
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• 2000

The objective of this research is to detect the papaya fruits on tree in an orchard. The detection of papaya on natural background is difficult because colors of fruits and background such as leaves are similarly green. We cannot separate it from leaves by color information. Therefore, this research will use shape information instead. First, we detect an interested object by detecting its boundary using edge detection technique. However, the edge detection will detect every objects boundary in the image. Therefore, shape description technique will be used to describe which one is the interested object boundary. The good shape description should be invariant in scaling, rotating, and translating. The successful concept is to use Fourier series, which is called "Fourier Descriptors". Elliptic Fourier Descriptors can completely represent any shape, which is selected to describe the shape of papaya. From the edge detection image, it takes a long time to match every boundary directly. The pre-processing task will reduce non-papaya edge to speed up matching time. The deformable template is used to optimize the matching. Then, clustering the similar shapes by the distance between each centroid, papaya can be completely detected from the background.

• Journal of Veterinary Clinics
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• v.17 no.2
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• pp.411-415
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• 2000

For comparison with conventional barium-gastrointestinal study, modified method using barium and methylcellulose was performed in 16 normal dogs (4-8 kg) divided into two groups. The group 1 received 8ml/kg of 40% w/v barium suspension only, and group 2 had taken 15 ml/kg of 0.6% w/v methylcellulose after administration 4 ml/kg of 40% w/v barium suspension by feeding tube. The barium suspension was prepared mixing full strength-barium suspension with water and methylcellulose solution was produced by blending methylcellulose sterilized water Sequential radiographs, lateral and ventrodorsal projections were obtained at 5 minute, 20 minute,40 minute. 60 minute and every 30 minutes thereafter, until the contrast is seen in the large intestine Inage qual- ity was rated by three veterinary radiologists as " poor" " fair ". "good", or "excellent" We analyzed the relationship between image quality,, transit time. Between two techniques, the modified method with 4ml of 40% w/v barium suspension and 15 ml of 0.6% w/v methylcellulose showed much better image quality ["excellent" result in 7 of the 8 subjects (88%)] and shorter transit time (107 minutes) toe the cecum. In addition, the best image quality was obtained at 20 and 40 minutes after admin-istration of contrast agent. It call be concluded the modified gastrointestinal study using methylcel-lulose after administration of barium suspension was a simple technique and easily improved the image quality and diagnostic accuracy of gstrointestinal disorders in small animal.racy of gstrointestinal disorders in small animal.

• Spatial Information Research
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• v.21 no.1
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• pp.63-73
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• 2013

Geographic features are reflected in satellite images, which contain characteristic elements. Information on changes can be obtained through a comparison of images taken at different times. If multi-temporal images can be classified through the use of an unsupervised method, this is likely to improve the accuracy of image classification and contribute to various applications. A rule-based image classification algorithm for automatic processing without human involvement has been developed, but it must be verified that its results are not affected by imperfect elements. In this study, Landsat images of Jeju Island were used to carry out a rule-based image classification. The application results were examined for complex cases, including the presence of clouds in the images, different photographed times, and the type of target area, such as city, mountain, or field. The presence of clouds did not affect calculations, and appropriate classification rules were applied, depending on the different photographed times. The expansion of the urban areas of Jeju and the increase of facilities such as vinyl greenhouses in Seoguipo were identified. Furthermore, space information changes and accurate classifications for Jeju Island were obtained. With the goal of performing high-quality unsupervised classifications, measures to generalize and improve the methods employed were searched for. The findings of this study could be used in time-series analyses of images for various applications, including urban development and environmental change monitoring.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1357-1369
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• 2022

Cloud removal is an essential image processing step for any task requiring time-series optical images, such as vegetation monitoring and change detection. This paper presents a two-stage cloud removal method that combines conditional generative adversarial networks (cGANs) with regression-based calibration to construct a cloud-free time-series optical image set. In the first stage, the cGANs generate initial prediction results using quantitative relationships between optical and synthetic aperture radar images. In the second stage, the relationships between the predicted results and the actual values in non-cloud areas are first quantified via random forest-based regression modeling and then used to calibrate the cGAN-based prediction results. The potential of the proposed method was evaluated from a cloud removal experiment using Sentinel-2 and COSMO-SkyMed images in the rice field cultivation area of Gimje. The cGAN model could effectively predict the reflectance values in the cloud-contaminated rice fields where severe changes in physical surface conditions happened. Moreover, the regression-based calibration in the second stage could improve the prediction accuracy, compared with a regression-based cloud removal method using a supplementary image that is temporally distant from the target image. These experimental results indicate that the proposed method can be effectively applied to restore cloud-contaminated areas when cloud-free optical images are unavailable for environmental monitoring.