• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.30 no.4C
• /
• pp.223-229
• /
• 2005

In this paper, we proposed an extended edge-based line averaging method for deinterlacing with restricted search range. Conversion from interlaced signal to non-interlaced signal is one of important issues. Conventional deinterlacing algorithms usually utilize edge-based line average algorithm(ELA) within pixel-by-pixel approach. However, it is very sensitive to noise and variation of intensity. To reduce the sensitivity, the proposed method adopts a block-by-block approach and provides reliable direction of edge. Simulation results show that it provides a better performance than other pixel-by-pixel ELA-based methods.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.15 no.11
• /
• pp.1062-1068
• /
• 2004

In the frequency range where the magnetostatic surface wave may be excited, the edge singularity of a microstrip line having a farrite layer is calculated by using the method proposed by Meixner. From the calculated edge singularity, the change of the current distribution near the edge to which the magnetostatic surface wave propagates is steeper than that near the other edge. And the edge conditions vary with frequency. These results agree with the previous numerical results.

• Journal of the Korean Society for Precision Engineering
• /
• v.16 no.8
• /
• pp.16-22
• /
• 1999

In this paper, an efficient algorithm for estimating real edge locations to subpixel values is described. Digital images are acquired by projection into image plane and sampling process. However, most of real edge locations are lost in this process, which causes low measurement accuracy. For accurate measurement, we propose an algorithm which estimates the real boundary between two adjacent pixels in digital imagery, with subpixel accuracy. We first define 1D edge operator based on the moment invariant. To extend it to 2D data, the edge orientation of each pixel is estimated by the LSE(Least Squares Error)line/circle fitting of a set of pixels around edge boundary. Then, using the pixels along the line perpendicular to the estimated edge orientation the real boundary is calculated with subpixel accuracy. Experimental results using real images show that the proposed method is robust in local noise, while maintaining low measurement error.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.7 no.5
• /
• pp.1033-1039
• /
• 2012

In this paper, a simple and robust algorithm is proposed for detecting each steel plate from a image which contains several steel plates. Steel plate is characterized by line edge, so line detection is a fundamental task for analyzing and understanding of steel plate images. To detect the line edge, the proposed algorithm uses the small eigenvalue analysis. The proposed approach scans an input edge image from the top left corner to the bottom right corner with a moving mask. A covariance matrix of a set of edge pixels over a connected region within the mask is determined and then the statistical and geometrical properties of the small eigenvalue of the matrix are explored for the purpose of straight line detection. Using the detected line edges, each plate is determined based on the directional information and the distance information of the line edges. The results of the experiments emphasize that the proposed algorithm detects each steel plate from a image effectively.

• Proceedings of the KSRS Conference
• /
• 1999.11a
• /
• pp.411-420
• /
• 1999

In geology, lineament features have been used to identify geological events, and many of scientists have been developed the algorithm that can be applied with the computer to recognize the lineaments. We choose several edge detection filter, line detection filters and Hough transform to detect an edge, line, and to vectorize the extracted lineament features, respectively. firstly the edge detection filter using a first-order derivative is applied to the original image In this step, rough lineament image is created Secondly, line detection filter is used to refine the previous image for further processing, where the wrong detected lines are, to some extents, excluded by using the variance of the pixel values that is composed of each line Thirdly, the thinning process is carried out to control the thickness of the line. At last, we use the Hough transform to convert the raster image to the vector one. A Landsat image is selected to extract lineament features. The result shows the lineament well regardless of directions. However, the degree of extraction of linear feature depends on the values of parameters and patterns of filters, therefore the development of new filter and the reduction of the number of parameter are required for the further study.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
• /
• 1997.04a
• /
• pp.323-325
• /
• 1997

Conventionally it is asummed that the microstrip line conductor has a rectangular cross-section. but the additive and substactive processes used to create conductors for PCBs produce a conductor of approximately Trapezoidal cross-section. For wide Strip line, the thickness and edge effect will be small since most of capacitance is parallel plate rather than fringing and we can ignore the cross-section. For narrow strip lines, the edge effect become immportant. So in this paper, we measure the chracteristic impedance of microstripline by Vector Analyzer and simulate the electromagnetic field of microstripline using finite element method with edge angle.

• Journal of Korea Multimedia Society
• /
• v.18 no.10
• /
• pp.1164-1171
• /
• 2015

The edge preserving method is important for image storage and geometric transformation. In this paper, we propose a new edge preserving method using HOG-Guide filter for image segmentation. In our approach, we extract edge information using gradient histogram to set HOG guide line. Then, we use HOG guide line to smooth image. With two to four iterations of smoothing operations, we finally obtain desirable edge preserved image. Our experimental results showed good performances showing that our proposed method is better than other methods.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2007.06a
• /
• pp.197-200
• /
• 2007

Edge representing the boundary between two regions with the large brightness difference in image includes diverse information about object. Therefore, this information has been utilized in fields such as image segmentation and object recognition. There are many kinds of edge in according to duration time and the amplitude of brightness variation, and edge is generally detected through the differential. Recently, in fields of image processing and computer vision, edge detection methods have been proposed to use in specific applications. Hence, in this paper the wavelet function for improved edge detection properties was proposed and detected line-edge components of images and its performance was proven through simulations.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.11 no.6
• /
• pp.1156-1161
• /
• 2007

Edge representing the boundary between two regions with the large briskness difference in mage includes diverse information about object. Therefore, this information has been utilized in fields such as image segmentation and object recognition. There are many kinds of edge according to duration time and the amplitude of brightness variation and edge is generally detected through the differential. Recently, in fields of image processing and computer vision, edge detection methods have been proposed to use in specific applications. Hence, in this paper the wavelet function for improved edge detection properties was proposed and detected line-edge components of images and its performance was proven through simulations.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2012.05a
• /
• pp.869-870
• /
• 2012