• Title/Summary/Keyword: 에지검출

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Multi-View Wyner-Ziv Video Coding Based on Spatio-temporal Adaptive Estimation (시공간 적응적인 예측에 기초한 다시점 위너-지브 비디오 부호화 기법)

  • Lee, Beom-yong;Kim, Jin-soo
    • The Journal of the Korea Contents Association
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    • v.16 no.6
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    • pp.9-18
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    • 2016
  • This paper proposes a multi-view Wyner-Ziv Video coding scheme based on spatio-temporal adaptive estimation. The proposed algorithm is designed to search for a better estimated block with joint bi-directional motion estimation by introducing weights between temporal and spatial directions, and by classifying effectively the region of interest blocks, which is based on the edge detection and the synthesis, and by selecting the reference estimation block from the effective motion vector analysis. The proposed algorithm exploits the information of a single frame viewpoint and adjacent frame viewpoints, simultaneously and then generates adaptively side information in a variety of closure, and reflection regions to have a better performance. Through several simulations with multi-view video sequences, it is shown that the proposed algorithm performs visual quality improvement as well as bit-rate reduction, compared to the conventional methods.

A Method for Finger Vein Recognition using a New Matching Algorithm (새로운 정합 알고리즘을 이용한 손가락 정맥 인식 방법)

  • Kim, Hee-Sung;Cho, Jun-Hee
    • Journal of KIISE:Software and Applications
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    • v.37 no.11
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    • pp.859-865
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    • 2010
  • In this paper, a new method for finger vein recognition is proposed. Researchers are recently interested in the finger vein recognition since it is a good way to avoid the forgery in finger prints recognition and the inconveniences in obtaining images of the iris for iris recognition. The vein images are processed to obtain the line shaped vein images through the local histogram equalization and a thinning process. This thinned vein images are processed for matching, using a new matching algorithm, named HS(HeeSung) matching algorithm. This algorithm yields an excellent recognition rate when it is applied to the curve-linear images processed through a thinning or an edge detection. In our experiment with the finger vein images, the recognition rate has reached up to 99.20% using this algorithm applied to 650finger vein images(130person ${\times}$ 5images each). It takes only about 60 milliseconds to match one pair of images.

Development of an Accuracy-improved Vision Inspection System for BGA Solder Ball (정확도를 향상시킨 BGA 솔더볼 외관검사 기법 개발)

  • Huh, Kyung-Moo
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.47 no.6
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    • pp.80-85
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    • 2010
  • BGA 409 chip currently the most as a visual inspection of the exterior inspection is conducted. Human depending on visual inspection of the exterior inspection of the current state of testers, depending on how the test results because the change is difficult to expect reliable results. Therefore, the challenges of visual inspection of BGA solder balls to improve the visual inspection technique was developed. However, BGA solder ball size of the microstructure and the characteristics of the distinction between hard test the accuracy of the fall orientation error has a problem. In this paper BGA solder balls exterior inspection of the accuracy to improve the edge detection algorithm, the complement of features and only the comparison proposed a pattern-matching techniques, based on the characteristics of spatial configuration of the area by improving the standard error of the orientation proposed improvements.

Efficient Binary Wavelet Reconstruction for Binary Images (이진 영상을 위한 효율적인 이진 웨이블렛 복원)

  • Kang, Eui-Sung
    • The Journal of Korean Association of Computer Education
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    • v.5 no.4
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    • pp.43-52
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    • 2002
  • A theory of binary wavelets which are performed over binary field has been recently proposed. Binary wavelet transform (BWT) of binary images can be used as an alternative to the real-valued wavelet transform of binary images in image processing applications such as compression, edge detection, and recognition. The BWT, however, requires large amount of computations for binary wavelet reconstruction since its operation is accomplished by matrix multiplication. In this paper, an efficient binary wavelet reconstruction method which utilizes filtering operation instead of matrix multiplication is presented. Experimental results show that the proposed algorithm can significantly reduce the computational complexity of the BWT. For the reconstruction of an $N{\times}N$ image, the proposed technique requires only $2MN^2$ multiplications and $2N(M-1)^2$ additions when the filter length M, while the BWT needs $2N^3$ multiplications and $2N(N-1)^2$ additions.

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3D conversion of 2D video using depth layer partition (Depth layer partition을 이용한 2D 동영상의 3D 변환 기법)

  • Kim, Su-Dong;Yoo, Ji-Sang
    • Journal of Broadcast Engineering
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    • v.16 no.1
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    • pp.44-53
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    • 2011
  • In this paper, we propose a 3D conversion algorithm of 2D video using depth layer partition method. In the proposed algorithm, we first set frame groups using cut detection algorithm. Each divided frame groups will reduce the possibility of error propagation in the process of motion estimation. Depth image generation is the core technique in 2D/3D conversion algorithm. Therefore, we use two depth map generation algorithms. In the first, segmentation and motion information are used, and in the other, edge directional histogram is used. After applying depth layer partition algorithm which separates objects(foreground) and the background from the original image, the extracted two depth maps are properly merged. Through experiments, we verify that the proposed algorithm generates reliable depth map and good conversion results.

Image Tracking Based Lane Departure Warning and Forward Collision Warning Methods for Commercial Automotive Vehicle (이미지 트래킹 기반 상용차용 차선 이탈 및 전방 추돌 경고 방법)

  • Kim, Kwang Soo;Lee, Ju Hyoung;Kim, Su Kwol;Bae, Myung Won;Lee, Deok Jin
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.39 no.2
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    • pp.235-240
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    • 2015
  • Active Safety system is requested on the market of the medium and heavy duty commercial vehicle over 4.5ton beside the market of passenger car with advancement of the digital equipment proportionally. Unlike the passenger car, the mounting position of camera in case of the medium and heavy duty commercial vehicle is relatively high, it is disadvantaged conditions for lane recognition in contradiction to passenger car. In this work, we show the method of lane recognition through the Sobel edge, based on the spatial domain processing, Hough transform and color conversion correction. Also we suggest the low error method of front vehicles recognition in order to reduce the detection error through Haar-like, Adaboost, SVM and Template matching, etc., which are the object recognition methods by frontal camera vision. It is verified that the reliability over 98% on lane recognition is obtained through the vehicle test.

Personal Identification Using One Dimension Iris Signals (일차원 홍채 신호를 이용한 개인 식별)

  • Park, Yeong-Gyu;No, Seung-In;Yun, Hun-Ju;Kim, Jae-Hui
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.39 no.1
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    • pp.70-76
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    • 2002
  • In this paper, we proposed a personal identification algorithm using the iris region which has discriminant features. First, we acquired the eye image with the black and white CCD camera and extracted the iris region by using a circular edge detector which minimizes the search space for real center and radius of the iris. And then, we localized the iris region into several circles and extracted the features by filtering signals on the perimeters of circles with one dimensional Gabor filter We identified a person by comparing ,correlation values of input signals with the registered signals. We also decided threshold value minimizing average error rate for FRR(Type I)error rate and FAR(Type II)error rate. Experimental results show that proposed algorithm has average error rate less than 5.2%.

Facial Image Recognition Based on Wavelet Transform and Neural Networks (웨이브렛 변환과 신경망 기반 얼굴 인식)

  • 임춘환;이상훈;편석범
    • Journal of the Institute of Electronics Engineers of Korea TE
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    • v.37 no.3
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    • pp.104-113
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    • 2000
  • In this study, we propose facial image recognition based on wavelet transform and neural network. This algorithm is proposed by following processes. First, two gray level images is captured in constant illumination and, after removing input image noise using a gaussian filter, differential image is obtained between background and face input image, and this image has a process of erosion and dilation. Second, a mask is made from dilation image and background and facial image is divided by projecting the mask into face input image Then, characteristic area of square shape that consists of eyes, a nose, a mouth, eyebrows and cheeks is detected by searching the edge of divided face image. Finally, after characteristic vectors are extracted from performing discrete wavelet transform(DWT) of this characteristic area and is normalized, normalized vectors become neural network input vectors. And recognition processing is performed based on neural network learning. Simulation results show recognition rate of 100 % about learned image and 92% about unlearned image.

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Implementation of an Effective Human Head Tracking System Using the Ellipse Modeling and Color Information (타원 모델링과 칼라정보를 이용한 효율적인 머리 추적 시스템 구현)

  • Park, Dong-Sun;Yoon, Sook
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.38 no.6
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    • pp.684-691
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    • 2001
  • In this paper, we design and implement a system which recognizes and tracks a human head on a sequence of images. In this paper, the color of the skin and ellipse modeling is used as feature vectors to recognize the human head. And the modified time-varying edge detection method and the vertical projection method is used to acquire regions of the motion from images with very complex backgrounds. To select the head from the acquired candidate regions, the process for thresholding on the basis of the I-component of YIQ color information and mapping with ellipse modeling is used. The designed system shows an excellent performance in the cases of the rotated heads, occluded heads, and tilted heads as well as in the case of the normal up-right heads. And in this paper, the combinational technique of motion-based tracking and recognition-based tracking is used to track the human head exactly even though the human head moves fast.

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Recognition of Concrete Surface Cracks Using Enhanced Max-Min Neural Networks (개선된 Max-Min 신경망을 이용한 콘크리트 균열 인식)

  • Kim, Kwang-Baek;Park, Hyun-Jung
    • Journal of the Korea Society of Computer and Information
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    • v.12 no.2 s.46
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    • pp.77-82
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    • 2007
  • In this paper, we proposed the image processing techniques for extracting the cracks in a concrete surface crack image and the enhanced Max-Min neural network for recognizing the directions of the extracted cracks. The image processing techniques used are the closing operation or morphological techniques, the Sobel masking for extracting for edges of the cracks, and the iterated binarization for acquiring the binarized image from the crack image. The cracks are extracted from the concrete surface image after applying two times of noise reduction to the binarized image. We proposed the method for automatically recognizing the directions of the cracks with the enhanced Max-Min neural network. Also, we propose an enhanced Max-Min neural network by auto-tuning of learning rate using delta-bar-delta algorithm. The experiments using real concrete crack images showed that the cracks in the concrete crack images were effectively extracted and the enhanced Max-Min neural network was effective in the recognition of direction of the extracted cracks.

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