• Journal of the Korean Society for Precision Engineering
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• v.24 no.2 s.191
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• pp.86-94
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• 2007

In this paper, a dual stage servo mechanism has been developed for image tracking system to improve control performances such as small rise time, small overshoot, small settling time, small stabilization error etc. A secondary stage, a platform, actuated by a pair of electro-magnets is mounted on a conventional elevation gimbal. In this mechanism, the gimbal provides large range but slow motion and the platform provides small range but fast positioning. A sliding mode control is applied to the platform positioning to attain robust performances and stability in the presence of the disturbance related to dynamic coupling of the gimbal and the platform. Results from experiments illustrate that the suggested dual stage mechanism controlled by the sliding mode control is effective in improving responses and attenuating the disturbance response related with dynamic coupling.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.29 no.2
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• pp.51-57
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• 2006

This study is concerned with image information management system for small scale hospital. We intended to developing image management system which is used of the existing analog devices such as medical camera, supersonic analyser, endoscope etc. We developed a video in interface board based USB 2.0 for handling image in real time. It is capable of transmitting image input signal like as NTSC, PAL to personal computer through USB 2.0. The developed the board of 40 speeds compared with the exiting system based USB 1.0. Especially the developed system is very helpful for small hospital like as dental clinic, because it is easy and convenient to manage image information without expert. So it will provide reduction of time and cost for handling image information(collecting, saving, retrieval, transmitting image).

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.12
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• pp.1189-1195
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• 2014

This paper addresses a Moving Target Indication (MTI) algorithm which can be used for small Unmanned Aerial Vehicles (UAVs) equipped with image sensors. MTI is a system (or an algorithm) which detects moving objects. The principle of the MTI algorithm is to analyze the difference between successive image data. It is difficult to detect moving objects in the images recorded from dynamic cameras attached to moving platforms such as UAVs flying at low altitudes over a variety of terrain, since the acquired images have two motion components: 'camera motion' and 'object motion'. Therefore, the motion of independent objects can be obtained after the camera motion is compensated thoroughly via proper manipulations. In this study, the camera motion effects are removed by using wiener filter-based image registration, one of the non-parametric methods. In addition, an image pyramid structure is adopted to reduce the computational complexity for UAVs. We demonstrate the effectiveness of our method with experimental results on outdoor video sequences.

• IEMEK Journal of Embedded Systems and Applications
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• v.13 no.5
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• pp.253-259
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• 2018

Recently, small satellite industries are rapidly changing. Demand for high performance small satellites is increasing with the expansion of Earth Observation Satellite market. A next-generation small satellites require a higher resolution image storage capacity than before. However, there is a problem that the HW configuration of the existing small satellite image storage device could not meet these requirements. The conventional data storing system uses SDRAM to store image data taken from satellites. When SDRAM is used in small satellite platform of a next generation, there is a problem that the cost of physical space is eight times higher and satellite price is two times higher than NAND Flash. Using the same satellite hardware configuration for next-generation satellites will increase the satellite volume to meet hardware requirements. Additional cost is required for structural design, environmental testing, and satellite launch due to increasing volume. Therefore, in order to construct a low-cost, high-efficiency system. This paper shows a next-generation solid state recorder unit (SSRU) using MRAM and NAND Flash instead of SDRAM. As a result of this research, next generation small satellite retain a storage size and weight and improves the data storage space by 15 times and the storage speed by 4.5 times compare to conventional design. Also reduced energy consumption by 96% compared to SDRAM based storage devices.

• Fashion & Textile Research Journal
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• v.7 no.2
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• pp.135-142
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• 2005

Through the formative analysis of the traditional jokakbo, we have composed surface composition that was made by a perfect square, triangle, a weather vane type, vertical type, cint$\tilde{a}$mani type, and a mixed rectangular. And we have composed that was made by vivid tone, pale tone, and so on, and finally analyzed image, preference rate of them. First, the cause of composition for the image of stimulant was composed by the cause of simplicity characteristics, interesting characteristics, rigid-flexibility characteristics, and modern characteristics. Secondly, the image of clothes was revealed as a simple image of perfect square, a feminine image of cint$\tilde{a}$mani type, a modern image of mixed rectangular in the case of large pattern. And in the case of small pattern, perfect square was revealed as a simple image, cint$\tilde{a}$mani type was revealed as a feminine image, triangle with achromatic colored weather vane type and pale tone was revealed as an interesting image, achromatic colored and pale toned a weather vane type, vivid toned vertical type was revealed as a modern image. Lastly, it revealed that the preference rate against clothes is related with the cause of simplicity characteristics, interesting characteristics, and rigid-flexibility characteristics in the case of large patterns, and especially in the case of large patterns and small patterns, the clothes of pale tone are more preferred. And achromatic colored mixed rectangular and chromatic colored cint$\tilde{a}$mani type are more preferred by the large patterns, and chromatic colored and pale toned weather vane type is more preferred by the small patterns.

• Journal of Korea Multimedia Society
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• v.23 no.6
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• pp.756-764
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• 2020

A typical algorithm used for image analysis is the Convolutional Neural Network(CNN). R-CNN, Fast R-CNN, Faster R-CNN, etc. have been studied to improve the performance of the CNN, but they essentially require large amounts of data and high algorithmic complexity., making them inappropriate for small and medium-sized services. Therefore, in this paper, the image label prediction algorithm based on CNN with collaborative layer with low complexity, high accuracy, and small amount of data was proposed. The proposed algorithm was designed to replace the part of the neural network that is performed to predict the final label in the existing deep learning algorithm by implementing collaborative filtering as a layer. It is expected that the proposed algorithm can contribute greatly to small and medium-sized content services that is unsuitable to apply the existing deep learning algorithm with high complexity and high server cost.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.8
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• pp.147-159
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• 1994

The performance of the improvement method of spatial resolution for satellite images based on the generalized inverse matrix is superior to the conventional methods. But, this method calculates the coefficient values for extracting the spatial information from the relation between a small pixel and large pixels. Accordingly it has the problem of remaining the blocky patterns at the result image. In this paper, a new generalized inverse matrix method is proposed which is different in the calculation method of coefficient values for extracting the spatial information. In this proposed metod, it calculates the coefficient values for extracting the spatial information from the relation between a small pixel and small pixels. Consequently it can improve the spatial resolution more efficiently without remaining the blocky patterns at the result image. The effectiveness of the proposed method is varified by simulation experiments with real TM image data.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.557-558
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• 2021

In this paper, we propose a new image classification method based on Convolutional Neural Network (CNN), which is mainly used to solve model overfitting and non-convergence and to improve classification accuracy in image classification tasks on small datasets.

• Journal of The Institute of Information and Telecommunication Facilities Engineering
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• v.9 no.2
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• pp.73-79
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• 2010

The most popular technique for image retrieval in a heterogeneous collection of color images is the comparison of images based on their color histogram. The color histogram describes the distribution of colors in the color space of a color image. In the most image retrieval systems, the color histogram is used to compute similarities between the query image and all the images in a database. But, small changes in the resolution, scaling, and illumination may cause important modifications of the color histogram, and so two color images may be considered to be very different from each other even though they have completely related semantics. A new method of color feature representation based on the 3-dimensional RGB color map is proposed to improve the defects of the color histogram. The proposed method is based on the three 2-dimensional projection map evaluated by projecting the RGB color space on the RG, GB, and BR surfaces. The experimental results reveal that the proposed is less sensitive to small changes in the scene and that achieve higher retrieval performances than the traditional color histogram.

• Journal of information and communication convergence engineering
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• v.2 no.2
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• pp.123-127
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• 2004

The most popular technique for image retrieval in a heterogeneous collection of color images is the comparison of images based on their color histogram. The color histogram describes the distribution of colors in the color space of a color image. In the most image retrieval systems, the color histogram is used to compute similarities between the query image and all the images in a database. But, small changes in the resolution, scaling, and illumination may cause important modifications of the color histogram, and so two color images may be considered to be very different from each other even though they have completely related semantics. A new method of color feature representation based on the 3-dimensional RGB color map is proposed to improve the defects of the color histogram. The proposed method is based on the three 2-dimensional projection map evaluated by projecting the RGB color space on the RG, GB, and BR surfaces. The experimental results reveal that the proposed is less sensitive to small changes in the scene and that achieve higher retrieval performances than the traditional color histogram.