• Title/Summary/Keyword: LoG

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Medial Axis Detection of Stripes Using LoG Scale-Space (LoG Scale-Space를 이용한 라인의 중심축 검출)

  • Byun, Ki-Won;Nam, Ki-Gon;Joo, Jae-Heum
    • Journal of the Institute of Convergence Signal Processing
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    • v.11 no.3
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    • pp.183-188
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    • 2010
  • In this paper we propose a detection method of the medial axis of the continuous stripes on the LoG scale-space. Our method detects the medial axis of continuous stripes iteratively by varying the scale of LoG operator. Small-scale LoG operator detects two +/- pole pairs centered on the edge positions of stripe by the zero-crossing detection. The more increase the scale of LoG scale-space, the more close two poles to the medial axis of stripe. The medial axis of continuous stripe is the position where two poles is overlapped. The proposed method detected robustly the medial axis of continuous stripes stronger than the thinning methods used to binary image.

Design of New Fine Dust Measurement Method applying LoG Edge Detection Technique (LoG 윤곽선 검출 기법을 적용한 새로운 미세먼지 측정 방법 설계)

  • Jang, Taek-Jin;Lin, Chi-Ho
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.22 no.5
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    • pp.69-73
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    • 2022
  • In this paper, we propose a new method for measuring fine dust through a LoG(Laplacian of Gaussian)-based edge detection technique. CCTV-based images in a video are collected for fine dust measurement, and image ranges are designated through RoI(Region of Interest). After clustering by applying the GMM(Gaussian Mix Model) to the specified area, we detect edge through the LoG algorithm and measure the detected edge strength. The concentration of fine dust is determined based on the measured intensity data of the edge. In this paper, we propose algorithm as the effectiveness of experiment. As a result of collecting and applying CCTV image in the video installed around the laboratory of this school for a month from June to July, the measured result value was proved through this experiment to be sufficient to calculate the concentration and range of fine dust.

A Comparative Study and Analysis of LoRaWAN Performance in NS3

  • Arshad Farhad;Jae-Young Pyun
    • Smart Media Journal
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    • v.13 no.1
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    • pp.45-51
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    • 2024
  • Long Range Wide Area Network (LoRaWAN) is a widely adopted Internet of Things (IoT) protocol due to its high range and lower energy consumption. LoRaWAN utilizes Adaptive Data Rate (ADR) for efficient resource (e.g., spreading factor and transmission power) management. The ADR manages these two resource parameters on the network server side and end device side. This paper focuses on analyzing the ADR and Gaussian ADR performance of LoRaWAN. We have performed NS3 simulation under a static scenario by varying the antenna height. The simulation results showed that antenna height has a significant impact on the packet delivery ratio. Higher antenna height (e.g., 50 m) has shown an improved packet success ratio when compared with lower antenna height (e.g., 10 m) in static and mobility scenarios. Based on the results, it is suggested to use the antenna at higher allevation for successful packet delivery.

3D Segmentation of a Diagnostic Object in Ultrasound Images Using LoG Operator (초음파 영상에서 LoG 연산자를 이용한 진단 객체의 3차원 분할)

  • 정말남;곽종인;김상현;김남철
    • Journal of Biomedical Engineering Research
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    • v.24 no.4
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    • pp.247-257
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    • 2003
  • This paper proposes a three-dimensional (3D) segmentation algorithm for extracting a diagnostic object from ultrasound images by using a LoG operator In the proposed algorithm, 2D cutting planes are first obtained by the equiangular revolution of a cross sectional Plane on a reference axis for a 3D volume data. In each 2D ultrasound image. a region of interest (ROI) box that is included tightly in a diagnostic object of interest is set. Inside the ROI box, a LoG operator, where the value of $\sigma$ is adaptively selected by the distance between reference points and the variance of the 2D image, extracts edges in the 2D image. In Post processing. regions of the edge image are found out by region filling, small regions in the region filled image are removed. and the contour image of the object is obtained by morphological opening finally. a 3D volume of the diagnostic object is rendered from the set of contour images obtained by post-processing. Experimental results for a tumor and gall bladder volume data show that the proposed method yields on average two times reduction in error rate over Krivanek's method when the results obtained manually are used as a reference data.

Color Filter Interpolation Algorithm using Laplacian of Gaussians (LoG) and Canny Edge Detection Method (Laplacian of Gaussians (LoG)와 캐니 에지 검출법을 접목한 색상 보간 알고리듬)

  • Choi, Yeonhee;Kim, Ilseung;Jeong, Jechang
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2014.11a
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    • pp.130-133
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    • 2014
  • 본 논문은 Laplacian of Gaussians (LoG)에 캐니 에지 검출 기법을 접목한 새로운 색상 보간 알고리듬을 제안한다. 캐니 에지 검출 기법은 영상 스무딩, 기울기 크기와 각도 계산, 세션화, 이중 문턱치 처리 과정으로 이루어진다. 이때 앞의 두 과정을 LoG를 이용하여 처리함으로써 기존의 캐니 애지 검출법보다 정확한 방향 정보를 얻을 수 있다. 실험결과를 통해 기존의 색상 보간 알고리듬에 비해 Peak Signal to Noise Ratio (CPSNR)이 상승함을 확인하였으며, 에지 영역 주변에서 발생하였던 무지개 에러가 현저히 감소하였음을 확인할 수 있었다.

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Comparison of LoG and DoG for 3D reconstruction in haptic systems (햅틱스 시스템용 3D 재구성을 위한 LoG 방법과 DoG 방법의 성능 분석)

  • Sung, Mee-Young;Kim, Ki-Kwon
    • Journal of Korea Multimedia Society
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    • v.15 no.6
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    • pp.711-721
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    • 2012
  • The objective of this study is to propose an efficient 3D reconstruction method for developing a stereo-vision-based haptics system which can replace "robotic eyes" and "robotic touch." The haptic rendering for 3D images requires to capture depth information and edge information of stereo images. This paper proposes the 3D reconstruction methods using LoG(Laplacian of Gaussian) algorithm and DoG(Difference of Gaussian) algorithm for edge detection in addition to the basic 3D depth extraction method for better haptic rendering. Also, some experiments are performed for evaluating the CPU time and the error rates of those methods. The experimental results lead us to conclude that the DoG method is more efficient for haptic rendering. This paper may contribute to investigate the effective methods for 3D image reconstruction such as in improving the performance of mobile patrol robots.

Ginsenoside-Rp1-induced apolipoprotein A-1 expression in the LoVo human colon cancer cell line

  • Kim, Mi-Yeon;Yoo, Byong Chul;Cho, Jae Youl
    • Journal of Ginseng Research
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    • v.38 no.4
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    • pp.251-255
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    • 2014
  • Background: Ginsenoside Rp1 (G-Rp1) is a novel ginsenoside derived from ginsenoside Rk1. This compound was reported to have anticancer, anti-platelet, and anti-inflammatory activities. In this study, we examined the molecular target of the antiproliferative and proapoptotic activities of G-Rp1. Methods: To examine the effects of G-Rp1, cell proliferation assays, propidium iodine staining, proteomic analysis by two-dimensional gel electrophoresis, immunoblotting analysis, and a knockdown strategy were used. Results: G-Rp1 dose-dependently suppressed the proliferation of colorectal cancer LoVo cells and increased their apoptosis. G-Rp1 markedly upregulated the protein level of apolipoprotein (Apo)-A1 in LoVo, SNU-407, DLD-1, SNU-638, AGS, KPL-4, and SK-BR-3 cells. The knockdown of Apo-A1 by its small-interfering RNA increased the levels of cleaved poly(ADP-ribose) polymerase and p53 and diminished the proliferation of LoVo cells. Conclusion: These results suggest that G-Rp1 may act as an anticancer agent by strongly inhibiting cell proliferation and enhancing apoptosis through upregulation of Apo-A1.

Multi Characters Detection Using Color Segmentation and LoG operator characteristics in Natural Scene (자연영상에서 컬러분할과 LoG연산특성을 이용한 다중 문자 검출에 관한 연구)

  • Shin, Seong;Baek, Young-Hyun;Moon, Sung-Ryong
    • Journal of the Korean Institute of Intelligent Systems
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    • v.18 no.2
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    • pp.216-222
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    • 2008
  • This paper proposed the multi characters detection algorithm using Color segmentation and the closing curve feature of LoG Operator in order to complement the demerit of the existing research which is weak in complexity of background, variety of light and disordered line and similarity of left and background color, etc. The proposed multi characters detection algorithm divided into three parts : The feature detection, characters format and characters detection Parts in order to be possible to apply to image of various feature. After preprocess that the new multi characters detection algorithm that proposed in this paper used wavelet, morphology, hough transform which is the synthesis logical model in order to raise detection rate by acquiring the non-perfection characters as well as the perfection characters with processing OR operation after processing each color area by AND operation sequentially. And the proposal algorithm is simulated with natural images which include natural character area regardless of size, resolution and slant and so on of image. And the proposal algorithm in this paper is confirmed to an excellent detection rate by compared with the conventional detection algorithm in same image.

Text Extraction Algorithm in Natural Image using LoG Operator and Coiflet Wavelet (Coiflet Wavelet과 LoG 연산자를 이용한 자연이미지에서의 텍스트 검출 알고리즘)

  • Shin, Seong;Baek, Young-Hyun;Moon, Sung-Ryong;Shin, Hong-Kyu
    • Proceedings of the IEEK Conference
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    • 2005.11a
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    • pp.979-982
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    • 2005
  • This paper is to be pre-processing that decides the text recognizability and quality contained in natural image. Differentiated with the existing studies, In this paper, it suggests the application of partially unified color models, Coiflet Wavelet and text extraction algorithm that uses the closed curve edge features of LoG (laplacian of gaussian)operator. The text image included in natural image such as signboard has the same hue, saturation and value, and there is a certain thickness as for their feature. Each color element is restructured into closed area by LoG operator, the 2nd differential operator. The text area is contracted by Hough Transform, logical AND-OR operator of each color model and Minimum-Distance classifier. This paper targets natural image into which text area is added regardless of the size and resolution of the image, and it is confirmed to have more excellent performance than other algorithms with many restrictions.

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Three Dimensional Building Construction Based on LIDAR Data (LIDAR 자료기반의 3차원 건물정보 구축)

  • Yoo, Hwan-Hee;Kim, Kyung-Whan;Kim, Seong-Sam
    • Journal of Korean Society for Geospatial Information Science
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    • v.14 no.3 s.37
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    • pp.13-22
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    • 2006
  • Realistic 3D building construction in urban area has become an important issue because of increasing demand of 3D geo-spatial information in many application. Contrary to the conventional 3D building model construction approach using aerial images and high-resolution satellite imagery, it has been researched widely in building reconstruction using high-accuracy aerial LIDAR data in the latest. This paper presents a method for 3D building construction through building outlines extraction by LoG operator's Zero-crossing and line generation and refinement by Douglas-Peucker algorithm.

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