• Information and Communications Magazine
• /
• v.32 no.7
• /
• pp.17-26
• /
• 2015

최근 네트워크 기술 동향에 있어서 이른바 핫 이슈 중 하나인 소프트웨어 정의 네트워킹(SDN, Software-Defined Networking)은 바야흐로 데이터센터, 기업, 캠퍼스 등의 근거리 데이터 네트워크(LAN, Local Area Network) 환경을 넘어서 통신망 사업자(캐리어)와 서비스 제공자를 통해 원거리 데이터 네트워크 (WAN, Wide Area Network)로 진화하고 있다. 본고에서는 종단간 SDN 프로덕션 서비스를 위한 소프트웨어 정의 원거리 네트워크(SD-WAN, Software-Defined WAN)의 개요 및 적용 사례를 소개하고, SD-WAN의 핵심 서비스 기술로 인식되고 있는 네트워크 최적화, 가상화, 자동화, SDX(Software-Defined Exchange) 등의 요소 기술과 연구 동향을 알아본다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2013.05a
• /
• pp.404-406
• /
• 2013

An image edge has been utilized as preprocessing procedure in various field such as object detection, object recognition. there are Sobel, Prewitt, Roberts, Laplacian as conventional edge detection methods. existing methods are implement is simple, but edge detection characteristics is insufficient in impulse noise area. Therefore, to compensate the defect of conventional methods, in this paper, an edge detection algorithm using modified mask is proposed.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.45 no.5
• /
• pp.18-24
• /
• 2008

In this paper we propose a novel method which improves digital image stabilization performance using adoptive selection of motion estimation area. Candidate area for motion estimation is decided and through two processes, multi image reference and edge energy distinction, final motion estimation area is selected. Then Motion estimation and compensation is following in selected area. Experimental results show that proposed method improves performance of digital image stabilization.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.10 no.3
• /
• pp.549-555
• /
• 2006

An edge detection is an very important area in image processing and computer vision, General edge detection methods (Robert mask, Sobel mask, Kirsh mask etc) are a good performance to detect step edge in a image but are no good performance to detect step edge in a noses image. We suggested a step edge detection method based on image information measure and neutral network. Using these essential properties of step edges, which are directional and structural and whose gray level distribution in neighborhood, as a input vector to the BP neutral network we get the good result of proposed algorithm. And also we get the satisfactory experimental result using rose image and cell images an experimental and analysing image.

• Korean Journal of Remote Sensing
• /
• v.33 no.5_1
• /
• pp.571-585
• /
• 2017

The number of spaceborne optical sensors including red-edge band has been increasing since red-edge band is known to be effective to enhance the information content on biophysical characteristics of vegetation. Considering that the Agriculture and Forestry Satellite is planning to carry an imaging sensor having red-edge band, we tried to analyze the current status and potential of red-edge band. As a case study, we analyzed the effect of using red-edge band and tried to find the optimum band width and wavelength region of the red-edge band to estimate leaf area index (LAI) of very dense tree canopy. Field spectral measurements were conducted from April to October over two tree species (white oak and pitch pine) having high LAI. Using the spectral measurement data, total 355 red-edge bands reflectance were simulated by varying five band width (10 nm, 20 nm, 30 nm, 40 nm, 50 nm) and 71 central wavelength. Two red-edge based spectral indices(NDRE, CIRE) were derived using the simulated red-edge band and compared with the LAI of two tree species. Both NDRE and CIRE showed higher correlation coefficients with the LAI than NDVI. This would be an alternative to overcome the limitation of the NDVI saturation problem that NDVI has not been effective to estimate LAI over very dense canopy situation. There was no significant difference among five band widths of red-edge band in relation to LAI. The highest correlation coefficients were obtained at the red-edge band of center wavelength near the 720 nm for the white oak and 710 nm for the pitch pine. To select the optimum band width and wavelength region of the red-edge band, further studies are necessary to examine the relationship with other biophysical variables, such as chlorophyll, nitrogen, water content, and biomass.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.33B no.4
• /
• pp.72-80
• /
• 1996

In this paper, variable windowing mean filter to remove speckle noise and a measure to detect thin edge in ultrasonic images are proposed. Because ultrasonic images are corrupted by speckle noise showing a granular appearance, good edge detection is difficult. As a result, noise removing filter is needed in preprocessing stage. The speckle noise removing filter is based on mean filter whose window size is changed by the ratio of standard deviation to mean for image signal and noise signal in local area. And the measure expressed the difference of means between tow windows is used for detecting thin edge in filtered image. Results show that variable windowing mean filter removes speckle noise effectively, and proposed measure is useful in detecting thin edge.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.24 no.10B
• /
• pp.1946-1952
• /
• 1999

A new image compression method to preserve edge characteristics in reconstructed images using an unsupervised learning neural is proposed in this paper. By the unsupervised competitive learning which generalizes previously proposed Centroid Neural Network(CNN) algorithm with the geometric characteristics of edge area and statistical characteristics of image data, more codevectors are allocated in the edge areas to provide the more accurate edges in reconstructed image. Experimental results show that the proposed method gives improved edge in reconstructed images when compared with SOM, Modified SOM and M/R-CNN.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.12 no.4
• /
• pp.308-318
• /
• 2012

Captions include information which relates to the images. In order to obtain the information in the captions, text extraction methods from images have been developed. However, most existing methods can be applied to captions with a fixed height or stroke width using fixed pixel-size or block-size operators which are derived from morphological supposition. We propose an edge connected components based method that can extract Korean captions that are composed of various sizes and fonts. We analyze the properties of edge connected components embedding captions and build a decision tree which discriminates edge connected components which include captions from ones which do not. The images for the experiment are collected from broadcast programs such as documentaries and news programs which include captions with various heights and fonts. We evaluate our proposed method by comparing the performance of the latent caption area extraction. The experiment shows that the proposed method can efficiently extract various sizes of Korean captions.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2001.10a
• /
• pp.767-770
• /
• 2001

Edge detection is one of issues with essential importance in the area of image process. An edge in image is a boundary or contour which a significant change occurs in image intensity. In the paper, we process edge detection algorithms which are based on Potts automata. The dynamical behavior of these automata is completely determined by Lyapunov operators for sequential and parallel update. If Potts Automata convergence to fixed points, then it can be used to image processing. From the generalized Potts automata point of view, we propose a Potts Automata technique for detecting edge. Based on the experimental results we discuss the advantage and efficiency.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2015.05a
• /
• pp.267-269
• /
• 2015

In the modern society, the images provide the most effective information in multi-devices and the edge includes important feature information in such images. This edge is used as an essential preconditioning process in several application fields and many studies have been carried out in order to obtain the excellent images. The methods of Sobel and Roberts which are generally known are simple to implement the images but bring more or less insufficient processing result. Thus, this paper proposed an edge detection algorithm using the area averaging of segmented mask in order to supplement the problems of the current methods and compared it with such current methods.