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Development for Automatic Thickness Measurment System by Digital Image Processing (디지탈 이미지 프로세싱을 이용한 자동두께 측정장치 개발)

  • 김영일;이상길
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 1993.10a
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    • pp.395-401
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    • 1993
  • The purpose of this paper is to develop an automatic measuring system based on the digital image processing which can be applied to the in-process measurement of the characteristics of the thin thickness. The derivative operators is used for edge detection in gray level image. This concept can be easiliy illustrated with the aid of object shows an image of a simple light object on a dark background, the gray level profile along a horizontal scan line of the image, and the first and second derivatives of the profile. The first derivative of an edge modeled in this manner is () in all regions of constant gray level, and assumes a constant value during a gray level transition. The experimental results indicate that the developed qutomatic inspection system can be applied in real situation.

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A Robust Method for Text Detection in Video (비디오에서 문자 검출을 위한 강인한 방법)

  • Dinh, Viet-Cuong;Jeon, Seung-Su;Ryu, Han-Jin;Seol, Sang-Hun
    • Proceedings of the Korean Information Science Society Conference
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    • 2007.06c
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    • pp.403-406
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    • 2007
  • This paper proposes an effective method for text detection in video. First, we apply an edge detection method to the video frame with a relative low threshold to keep all possible text edge pixels. Second, a multi-frame integration method is applied to significantly remove background pixels which are not stationary in a specific period. Finally, text regions are extracted by using the coarse to fine projection method. Experimental results demonstrate the effectiveness of the proposed method.

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Development for Automatic Thickness Measurment System by Digital Image Processing (디지탈 영상처리 기법을 이용한 자동 두께측정 장치 개발)

  • Kim, Y.I.
    • Journal of the Korean Society for Precision Engineering
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    • v.12 no.6
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    • pp.72-79
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    • 1995
  • The purpose of this paper is to develop an automatic measuring system based on the digital image processing which can be applied to the in-process measurment of the characteristics of the thin thickness. The derivative operators is used for edge detection in gray level image. This concept can be easily illustrated with the aid of object shows an image of a simple light object on a dark background, the gray level profile along a horizontal scan line of the image, and the first and second derivatives of the profile. The first derivative of an edge modeled in this manner is 0 in all regions of constant gray level, and assumes a constant value during a gray level transition. The experimental results indicate that the developed automatic inspection system can be applied in real situation.

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Vehicle Identification Number Recognition using Edge Projection and PCA (에지 투영과 PCA를 이용한 차대 번호 인식)

  • Ahn, In-Mo;Ha, Jong-Eun
    • Journal of Institute of Control, Robotics and Systems
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    • v.17 no.5
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    • pp.479-483
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    • 2011
  • The automation of production process is actively expanding for the purpose of the cost reduction and quality assurance. Among these, automatic tracking of the product along the whole process of the production is also important topic. Typically this is done by adopting OCR technology. Conventional OCR technology operates well on the rather good quality of the image like as printed characters on the paper. In industrial application, IDs are marked on the metal surface, and this cause the height difference between background material and character. Illumination systems that guarantee an image with good quality may be a solution, but it is rather difficult to design such an illumination system. This paper proposes an algorithm for the recognition of vehicle's ID characters using edge projection and PCA (Principal Component Analysis). Proposed algorithm robustly operates under illumination change using the same parameters. Experimental results show the feasibility of the proposed algorithm.

Car Identification Using Comparing Car Size (크기 비교를 통한 차량 식별)

  • Shin, Kwang-Seong;Shin, Seong-Yoon
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2019.05a
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    • pp.488-489
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    • 2019
  • We propose a method to identify vehicle type by the formula of distance between feature points of vehicle and proportional rate of size. Car images are converted from the basic RGB model to the gray color model. Perform Canny Edge Direction to remove the background image of the car. The desired feature points are obtained through contour extraction.

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Optimal Display Method Considering the Display Element and Color of Fire Shutter Door (방화셔터 출입구의 표시 요소 및 색상을 고려한 최적 표시방법)

  • Son, Jong-Yeong;Hong, Won-Hwa;Bae, Young-Hoon
    • Fire Science and Engineering
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    • v.32 no.2
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    • pp.67-72
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    • 2018
  • A fire shutter is installed to prevent the movement of fire or smoke when a fire occurs inside a building. Fire shutters have access doors for passengers. On the other hand, the present fire shutter door display regulation is only required to be displayed in a different color from the surroundings. Hence, the risk of people not being able to recognize the door of the fire shutter is quite high, and the danger increases further in a smoke situation. Therefore, this study attempted to find a way to mark a fire shutter door that can be recognized even when smoke is spreading. First, a preliminary questionnaire was used to draw three factors to mark the fire shutter door (sign, door background, and edge). The experiment type was set by combining 5 colors for the three derived factors. The experiment was conducted on a total of 122 male and female participants. The results showed that a yellow background, red sign, and red edge have the highest awareness in a normal visual field without smoke. This was also the same in the field of view in the case of a fire with smoke, but the red background, yellow sign, and yellow edge were most noticeable in the case of dark smoke.

A Robust Staff Line Height and Staff Line Space Estimation for the Preprocessing of Music Score Recognition (악보인식 전처리를 위한 강건한 오선 두께와 간격 추정 방법)

  • Na, In-Seop;Kim, Soo-Hyung;Nquyen, Trung Quy
    • Journal of Internet Computing and Services
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    • v.16 no.1
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    • pp.29-37
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    • 2015
  • In this paper, we propose a robust pre-processing module for camera-based Optical Music Score Recognition (OMR) on mobile device. The captured images likely suffer for recognition from many distortions such as illumination, blur, low resolution, etc. Especially, the complex background music sheets recognition are difficult. Through any symbol recognition system, the staff line height and staff line space are used many times and have a big impact on recognition module. A robust and accurate staff line height and staff line space are essential. Some staff line height and staff line space are proposed for binary image. But in case of complex background music sheet image, the binarization results from common binarization algorithm are not satisfactory. It can cause incorrect staff line height and staff line space estimation. We propose a robust staff line height and staff line space estimation by using run-length encoding technique on edge image. Proposed method is composed of two steps, first step, we conducted the staff line height and staff line space estimation based on edge image using by Sobel operator on image blocks. Each column of edge image is encoded by run-length encoding algorithm Second step, we detect the staff line using by Stable Path algorithm and removal the staff line using by adaptive Line Track Height algorithm which is to track the staff lines positions. The result has shown that robust and accurate estimation is possible even in complex background cases.

Salient Object Extraction from Video Sequences using Contrast Map and Motion Information (대비 지도와 움직임 정보를 이용한 동영상으로부터 중요 객체 추출)

  • Kwak, Soo-Yeong;Ko, Byoung-Chul;Byun, Hye-Ran
    • Journal of KIISE:Software and Applications
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    • v.32 no.11
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    • pp.1121-1135
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    • 2005
  • This paper proposes a moving object extraction method using the contrast map and salient points. In order to make the contrast map, we generate three-feature maps such as luminance map, color map and directional map and extract salient points from an image. By using these features, we can decide the Attention Window(AW) location easily The purpose of the AW is to remove the useless regions in the image such as background as well as to reduce the amount of image processing. To create the exact location and flexible size of the AW, we use motion feature instead of pre-assumptions or heuristic parameters. After determining of the AW, we find the difference of edge to inner area from the AW. Then, we can extract horizontal candidate region and vortical candidate region. After finding both horizontal and vertical candidates, intersection regions through logical AND operation are further processed by morphological operations. The proposed algorithm has been applied to many video sequences which have static background like surveillance type of video sequences. The moving object was quite well segmented with accurate boundaries.

A Study on the Individual Authentication Using Facial Information For Online Lecture (가상강의에 적용을 위한 얼굴영상정보를 이용한 개인 인증 방법에 관한 연구)

  • 김동현;권중장
    • Proceedings of the IEEK Conference
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    • 2000.11c
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    • pp.117-120
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    • 2000
  • In this paper, we suggest an authentication system for online lecture using facial information and a face recognition algorithm base on relation of face. First, a facial area on complex background is detected using color information. Second, features are extracted with edge profile. Third, compare it with the value of original facial image in database. By experiments, we know that the proposed system is an useful method for online lecture authentication system.

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HDR Tone Mapping Using Belief Propagation (신뢰도 전파를 이용한 HDR 영상의 동적 영역 압축)

  • Lee, Chul;Kim, Chang-Su
    • Proceedings of the IEEK Conference
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    • 2007.07a
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    • pp.267-268
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    • 2007
  • A dynamic range compression algorithm using Markov random field (MRF) modeling to display high dynamic range (HDR) images on low dynamic range (LDR) devices is proposed in this work. The proposed algorithm separates foreground objects from the background using the edge information, and then compresses the color differences across the edges based on the MRF modeling. By minimizing a cost function using belief propagation, the proposed algorithm can provide an effective LDR image. Simulation results show that the proposed algorithm provides good results.

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