• Journal of Information Processing Systems
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• v.15 no.1
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• pp.7-21
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• 2019

In order to improve the edge segmentation effect of the level set image segmentation and avoid the influence of the initial contour on the level set method, a saliency level set image segmentation model based on local Renyi entropy is proposed. Firstly, the saliency map of the original image is extracted by using saliency detection algorithm. And the outline of the saliency map can be used to initialize the level set. Secondly, the local energy and edge energy of the image are obtained by using local Renyi entropy and Canny operator respectively. At the same time, new adaptive weight coefficient and boundary indication function are constructed. Finally, the local binary fitting energy model (LBF) as an external energy term is introduced. In this paper, the contrast experiments are implemented in different image database. The robustness of the proposed model for segmentation of images with intensity inhomogeneity and complicated edges is verified.

• Nuclear Engineering and Technology
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• v.55 no.2
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• pp.443-451
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• 2023

Machine Learning has introduced many solutions in data science, but its application in IoT faces significant challenges, due to the limitations in memory size and processing capability of constrained devices. In this paper we design an automatic gamma radiation detection and identification embedded system that exploits the power of TinyML in a SiPM micro radiation sensor leveraging the Edge Impulse platform. The model is trained using real gamma source data enhanced by software augmentation algorithms. Tests show high accuracy in real time processing. This design has promising applications in general-purpose radiation detection and identification, nuclear safety, medical diagnosis and it is also amenable for deployment in small satellites.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.05a
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• pp.74-76
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• 2021

최근 정보통신기술의 발달과 개인 스마트기기 성능의 상향평준화로 멀티미디어 콘텐츠의 사용량이 증가하고 있다. 멀티미디어 서비스를 제공하는 기업들은 사용자 경험을 개선하기 위해 조회 수를 기준으로 우선순위를 부여하는 콘텐츠 배치 전략에 따라 엣지에 우선순위가 높은 콘텐츠를 배치한다. 이러한 방식은 우선순위가 아닌 콘텐츠들을 사용자에게 서비스할 때 콘텐츠 전달 속도가 증가한다. 본 논문에서는 이러한 차순위 콘텐츠들의 전달 속도를 개선하기 위하여 CDN 기반의 콘텐츠 선호도에 따른 Edge-Fog 연계 Caching 기법을 제안한다.

• Journal of the Korean Society for Precision Engineering
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• v.11 no.5
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• pp.124-133
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• 1994

Many of non-contact measuring systems are used to estimate surface characteristics owing to their advantages of high speed and undanaged test. In this paper, a new measuring system is proposed to acquire image from CCD camera through back light illumination. Lowpass filter is very useful in view of noise removal and optimum binary image can be made through histogram equalization which is one of the histogram technique to maximize brightness intensity between workpiece and background. Laplacian operator is used to detect workpiece edge from binary image. In case of image treatment applying Laplacian operator, surface roughness is calculated by introducing conversion coefficient for coordinate of pixel which edge is composed of. In summary, the work is concerned with the development of a new technique for roughness measurement by the image processing in turning.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.11a
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• pp.589-592
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• 2020

본 논문은 스마트 해상 물류에 필요한 최신 Edge Computing과 인공지능을 구성한 자율 접안 시뮬레이터의 개발이다. 먼저, 스마트 해상 물류에서 선박의 접안에 관한 요구 사항을 분석하고, 다음으로 그 분석된 결과를 사용하여 서비스, 시스템, 핵심부품을 설계하고 제작한다. 결국, 본 논문은 스마트 해상물류에 필요한 자율접안 시뮬레이터를 개발한다. 향후, 본 논문은 실제 스마트 해상 물류에 필요한 Edge Computing과 인공지능의 기계 학습 알고리즘을 개발할 계획이다.

• Journal of Information Processing Systems
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• v.18 no.6
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• pp.803-812
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• 2022

With the increasing number of mobile device users worldwide, utilizing mobile edge computing (MEC) devices close to users for content caching can reduce transmission latency than receiving content from a server or cloud. However, because MEC has limited storage capacity, it is necessary to determine the content types and sizes to be cached. In this study, we investigate a caching strategy that increases the hit ratio from small base stations (SBSs) for mobile users in a heterogeneous network consisting of one macro base station (MBS) and multiple SBSs. If there are several SBSs that users can access, the hit ratio can be improved by reducing duplicate content and increasing the diversity of content in SBSs. We propose a Deep Q-Network (DQN)-based caching strategy that considers time-varying content popularity and content redundancy in multiple SBSs. Content is stored in the SBS in a divided form using maximum distance separable (MDS) codes to enhance the diversity of the content. Experiments in various environments show that the proposed caching strategy outperforms the other methods in terms of hit ratio.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.12 no.3
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• pp.89-95
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• 2003

This research analyzes the cutting mechanism of A1100-H18 of commercially pure aluminum by image processing in SEM(Scanning Electron Microscope) for the measurement of strain rate distribution near a cutting edge in orthogonal micro-cutting. The distribution is measured using various methods in order. The methods are in-situ observations of cutting process in SEM, inputting image data, a computer image processing, calculating displacements by SSDA(Sequential Similarity Detection Algorithm) and calculating strain rates by FEM. The min results obtained are as follows: (1)It enables to measure a microscopic displacement near a cutting edge. (2) An application of this system to cutting process of various materials will help to make cutting mechanism clear.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.40 no.2
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• pp.38-44
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• 2003

This paper describes the development of stand-alone image processing module on Strong Arm CPU employing an embedded Linux. Stand-alone image Processing module performs various functions such as thresholding, edge detection, and image enhancement of a raw image data in real time. The comparison of execution time between similar PC and developed module shows the satisfactory results. This Paper provides the possibility of applying embedded Linux successfully in industrial devices.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.1
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• pp.54-60
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• 2009

In this paper, a precision landing approach is implemented based on real-time image processing. A full-scale landmark for automatic landing is used. canny edge detection method is applied to identify the outside quadrilateral while circular hough transform is used for the recognition of inside circle. Position information on the ground landmark is uplinked to the unmanned helicopter via ground control computer in real time so that the unmanned helicopter control the air vehicle for accurate landing approach. Ground test and a couple of flight tests for autonomous landing approach show that the image processing and automatic landing operation system have good performance for the landing approach phase at the altitude of $20m{\sim}1m$ above ground level.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.10
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• pp.25-34
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• 1999

In this paper, an algorithm is presented to recognize lane and obstacles based on highway road image. The road images obtained by a video camera undergoes a pre-processing that includes filtering, edge detection, and identification of lanes. After this pre-processing, a part of image is grouped into 27 sub-windows and fed into a three-layer feed-forward neural network. The neural network is trained to indicate the road direction and the presence of absence of an obstacle. The proposed algorithm has been tested with the images different from the training images, and demonstrated its efficacy for recognizing lane and obstacles. Based on the test results, it can be said that the algorithm successfully combines the traditional image processing and the neural network principles towards a simpler and more efficient driver warning of assistance system