• Title/Summary/Keyword: Background Edge

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Object Segmentation Algorithm Using Disparity-Adaptive Diffusion (변이 적응 확산을 이용한 물체 분할 알고리즘)

  • 김은지;남기곤;이상찬
    • Proceedings of the Korea Institute of Convergence Signal Processing
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    • 2001.06a
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    • pp.249-252
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    • 2001
  • 본 논문에서는 실제 물체 윤곽을 검출하기 위해 물체 분할 과정에서 변이(disparity) 정보를 이용한다. 스테레오 정합(stereo matching)으로 획득한 변이도에서 불연 속한 부분은 물체의 경계나 변이가 할당되지 않는 폐색 영역 일부분에서 나타날 수 있으므로, 변이 변화가 작 은 영상의 각 영역은 같은 물체의 일부분이라는 것은 직관적으로 명백하다. 분할 과정은 이러한 변이 정보를 적절하게 이용하고 확산망(diffusion network)을 이용하여 선택적인 확산을 수행한다. 추정된 변이도는 변이 변화가 작은 영역을 인식하기 위해 사용되고 그러한 영 역은 단일 물체의 일부분이거나 배경(background)이라고 간주하고 텍스쳐(texture)에 의한 에지(edge)글 등방성 확산으로 제거하는 과정을 거친다. 나머지 영상 영역에서, 비등방성 확산으로 변이의 변화와 밝기차의 변화를 고려하여 수행된다.

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Noise Removal for Level Set based Flower Segmentation (레벨셋 기반 꽃 분할을 위한 노이즈 제거)

  • Park, Sang Cheol;Oh, Kang Han;Na, In Seop;Kim, Soo Hyung;Yang, Hyung Jeong;Lee, Guee Sang
    • Smart Media Journal
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    • v.1 no.2
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    • pp.34-39
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    • 2012
  • In this paper, post-processing step is presented to remove noises and develop a fully automated scheme to segment flowers in natural scene images. The scheme to segment flowers using a level set algorithm in the natural scene images produced unexpected and isolated noises because the level set relies only on the color and edge information. The experimental results shows that the proposed method successfully removes noises in the foreground and background.

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Development of System based on Digital Image Processing for Precision Measurement of Micro Spring (초소형 스프링 정밀 측정을 위한 디지털 영상 처리 시스템 개발)

  • 표창률;강성훈;전병희
    • Transactions of Materials Processing
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    • v.11 no.7
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    • pp.620-627
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    • 2002
  • The purpose of this paper is the development of an automated measurement system for micro spring based on the digital image processing technique. This micro spring can be used in various engineering applications such as filament, load bearing springs, hard disk suspension and many others. Main functionality of the micro spring inspection system is to measure the representative pitch of the micro spring. The derivative operators are used for edge detection in gray level image. Measurement system developed in this paper consisted of new auto feeding mechanism to take advantage of air pressure. In the process of development of the micro spring inspection system based on the image processing and analysis, strong background technology and know-how have been accumulated to measure micro mechanical parts.

A Study on the In-process Measurement of Surface Roughness by Image processing (이미지 프로세싱을 이용한 표면거칠기 인프로세스 측정에 관한 연구)

  • 소의열
    • Transactions of the Korean Society of Machine Tool Engineers
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    • v.10 no.5
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    • pp.1-8
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    • 2001
  • A measuring system is developed to acquire static image from rotary state through CCD camera in back light illumination by synchronizing chopper to workpiece. In image processing of acquired image, 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. After image treatment applying Laplacian operator, surface roughness is calculated by introducing conversion coefficient of pixel which edge is composed of.

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Trend of Human Vibration Research in Korea

  • Park, Hee-Sok
    • Journal of the Ergonomics Society of Korea
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    • v.32 no.4
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    • pp.293-295
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    • 2013
  • Objective: The objective of this study is to examine the characteristics of the research on human vibration in Korea. Background: There have been relatively less interests in vibration than other ergonomic factors in Korea. However, the importance of vibration is increasing as industry and everyday life are more mechanized. Method: This study reports the results of the literature review on the papers about human vibration published in ergonomics-related domestic journals. Results: It was found that more studies have been done on local vibration than on whole body vibration. Diverse topics have been studied in ergonomics community. Conclusion: Further cutting-edge studies are expected than classical safety and health related ones. Application: Some suggestions were proposed hopefully helpful to colleague ergonomists for future research.

Discrimination for Line-clustering Segmental Approach to Steel-tube X-ray Image (경사조사(傾斜照射) 강판튜브 방사선영상 영역특성 분석)

  • Hwang, Jung-Won;Hwang, Jae-Ho
    • Proceedings of the IEEK Conference
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    • 2007.07a
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    • pp.399-400
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    • 2007
  • This paper proposes an regional analytic approach in image data space for radiographic image. Image is segmented into four regions, such as background, thickness, weld area and tube area, due to directional properties. Each region has its own gray level distribution, contrast range and noise property, originated from X-ray project mechanism and electric control system itself. Projection incorrectness and noise influence included on imaging quality is analyzed functionally and statistically. The experimental results shows not only segmental effects, but also visual edge evaluation.

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A Study on the Position Tracking of Moving Image for Surveillance System (이동영상 위치추적 감시시스템에 관한 연구)

  • Lee Seung-Young;Jung Tae-Rim;Hur Chang-Wu;Ryu Kwang-Ryol
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2006.05a
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    • pp.205-208
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    • 2006
  • The position tracking of moving image for surveillance system is presented in this paper. The image of objects moving is detected with difference image between the background image not to be moved relatively and the forward moving image. The moving image is tracked with edge detection and moving vector to the object. The experiment result shows that the system enable to trail the position of moving objects obviously and is able to discriminate an infiltration.

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Recognition of Resistor Color Band Using a Color Segmentation in a HSI Color Model (HSI 색상 모델에서 색상 분할을 이용한 저항 색상 밴드 인식)

  • Jung, Min Chul
    • Journal of the Semiconductor & Display Technology
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    • v.18 no.2
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    • pp.67-72
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    • 2019
  • This paper proposes a new method for the recognition of resistor color band using a color segmentation in a HSI color model. The proposed method firstly segments a resistor in a chromatic color as a ROI from a background. Secondly, the color bands of the resistor are segmented by vertical projection profile using both the intensity and the saturation differentiation and finally, it recognizes the colors of the segmented color bands using hue, saturation and intensity values. The final results are the value of the resistor and the names of the recognized color. The proposed method is implemented using C language in Raspberry Pi system with a camera module for a real-time image processing. Experiments were conducted by using various resistor images. The results show that the proposed method is successful for the recognition of resistor color band.

Entropic Image Thresholding Segmentation Based on Gabor Histogram

  • Yi, Sanli;Zhang, Guifang;He, Jianfeng;Tong, Lirong
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.4
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    • pp.2113-2128
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    • 2019
  • Image thresholding techniques introducing spatial information are widely used image segmentation. Some methods are used to calculate the optimal threshold by building a specific histogram with different parameters, such as gray value of pixel, average gray value and gradient-magnitude, etc. However, these methods still have some limitations. In this paper, an entropic thresholding method based on Gabor histogram (a new 2D histogram constructed by using Gabor filter) is applied to image segmentation, which can distinguish foreground/background, edge and noise of image effectively. Comparing with some methods, including 2D-KSW, GLSC-KSW, 2D-D-KSW and GLGM-KSW, the proposed method, tested on 10 realistic images for segmentation, presents a higher effectiveness and robustness.

Multi-feature local sparse representation for infrared pedestrian tracking

  • Wang, Xin;Xu, Lingling;Ning, Chen
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.3
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    • pp.1464-1480
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    • 2019
  • Robust tracking of infrared (IR) pedestrian targets with various backgrounds, e.g. appearance changes, illumination variations, and background disturbances, is a great challenge in the infrared image processing field. In the paper, we address a new tracking method for IR pedestrian targets via multi-feature local sparse representation (SR), which consists of three important modules. In the first module, a multi-feature local SR model is constructed. Considering the characterization of infrared pedestrian targets, the gray and edge features are first extracted from all target templates, and then fused into the model learning process. In the second module, an effective tracker is proposed via the learned model. To improve the computational efficiency, a sliding window mechanism with multiple scales is first used to scan the current frame to sample the target candidates. Then, the candidates are recognized via sparse reconstruction residual analysis. In the third module, an adaptive dictionary update approach is designed to further improve the tracking performance. The results demonstrate that our method outperforms several classical methods for infrared pedestrian tracking.