• Title/Summary/Keyword: 적응적 에지 검출

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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.

Adaptive prototype generating technique for improving performance of a p-Snake (p-Snake의 성능 향상을 위한 적응 원형 생성 기법)

  • Oh, Seung-Taek;Jun, Byung-Hwan
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.16 no.4
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    • pp.2757-2763
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    • 2015
  • p-Snake is an energy minimizing algorithm that applies an additional prototype energy to the existing Active Contour Model and is used to extract the contour line in the area where the edge information is unclear. In this paper suggested the creation of a prototype energy field that applies a variable prototype expressed as a combination of circle and straight line primitives, and a fudge function, to improve p-Snake's contour extraction performance. The prototype was defined based on the parts codes entered and the appropriate initial contour was extracted in each primitive zones acquired from the pre-processing process. Then, the primitives variably adjusted to create the prototype and the contour probability based on the distance to the prototype was calculated through the fuzzy function to create the prototype energy field. This was applied to p-Snake to extract the contour from 100 images acquired from various small parts and compared its similarity with the prototype to find that p-Snake made with the adaptive prototype was about 4.6% more precise than the existing Snake method.

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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Adaptive Median Filter by Local Variance and Local Central Variance (로컬 분산과 로컬 중간값 분산을 이용한 적응형 메디안 필터)

  • 조우연;최두일
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.41 no.6
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    • pp.285-294
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    • 2004
  • Median Filters in the Signal Processing have been most widely used and have demonstrated the most strongest effects. This paper proposes the Adaptive Median Filters by using noise detection. The basic algorithm of the proposed filters is to determine whether noise or not by the each noise judgement standards, and then take the Median Filter if it satisfies the conditions as a result of judgement and returns to the original image(No Filters) if not. This paper presented Noise Detection by Local Variance and Local Central Variance for noise judgement, compared and analyzed the features and performance of existing [5]∼[10] Filters. Filter improved on the result of executing the existing filters at the same condition and showed the effects over that when it was judged with naked eyes. Accordingly, the Adaptive Median Filters by Local Variance and Local Central Variance was proven to have reinforced edge preservation ability and have the strong features for removing the Impulse Noise of the Median Filter.

Multipurpose Watermarking Scheme Based on Contourlet Transform (컨투어렛 변환 기반의 다중 워터마킹 기법)

  • Kim, Ji-Hoon;Lee, Suk-Hwan;Park, Seung-Seob;Kim, Ji-Hong;Oh, Sei-Woong;Seo, Yong-Su;Kwon, Ki-Ryong
    • Journal of Korea Multimedia Society
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    • v.12 no.7
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    • pp.929-940
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    • 2009
  • This paper presents multipurpose watermarking scheme in coutourlet transform domain for copyright protection, authentication and transform detection. Since contourlet transform can detect more multi direction edge and smooth contour than wavelet transform, the proposed scheme embeds multi watermarks in contourlet domain based on 4-level Laplacian pyramid and 2-level directional filter bank. In the first stage of the robust watermarking scheme for copyright protection, we generates the sequence of circle patterns according to watermark bits and projects these patterns into the average of magnitude coefficients of high frequency directional subbands. Then the watermark bit is embedded into variance distribution of the projected magnitude coefficients. In the second stage that is the semi-fragile watermarking scheme for authentication and transform detection, we embed the binary watermark image in the low frequency subband of higher level by using adaptive quantization modulation scheme. From the evaluation experiment using Checkmark 2.1, we verified that the proposed scheme is superior to the conventional scheme in a view of the robustness and the invisibility.

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Adaptive weight approach for stereo matching (적응적 가중치를 이용한 스테레오 정합 기법)

  • Yoon, Hee-Joo;Hwang, Young-Chul;Cha, Eui-Young
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2008.08a
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    • pp.73-76
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    • 2008
  • We present a area-based method for stereo matching using varying weights. A central problem in a area-based stereo matching is different result from selecting a window size. Most of the previous window-based methods iteratively update windows. However, the iterative methods very sensitive the initial disparity estimation and are computationally expensive. To resolve this problem, we proposed a new function to assign weights to pixels using features. To begin with, we extract features in a given stereo images based on edge. We adjust the weights of the pixels in a given window based on correlation of the stereo images. Then, we match pixels in a given window between the reference and target images of a stereo pair. The proposed method is compared to existing matching strategies using both synthetic and real images. The experimental results show the improved accuracy of the proposed method.

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Adaptive Vehicle License Plate Recognition System Using Projected Plane Convolution and Decision Tree Classifier (투영면 컨벌루션과 결정트리를 이용한 상태 적응적 차량번호판 인식 시스템)

  • Lee Eung-Joo;Lee Su Hyun;Kim Sung-Jin
    • Journal of Korea Multimedia Society
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    • v.8 no.11
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    • pp.1496-1509
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    • 2005
  • In this paper, an adaptive license plate recognition system which detects and recognizes license plate at real-time by using projected plane convolution and Decision Tree Classifier is proposed. And it was tested in circumstances which presence of complex background. Generally, in expressway tollgate or gateway of parking lots, it is very difficult to detect and segment license plate because of size, entry angle and noisy problem of vehicles due to CCD camera and road environment. In the proposed algorithm, we suggested to extract license plate candidate region after going through image acquisition process with inputted real-time image, and then to compensate license size as well as gradient of vehicle with change of vehicle entry position. The proposed algorithm can exactly detect license plate using accumulated edge, projected convolution and chain code labeling method. And it also segments letter of license plate using adaptive binary method. And then, it recognizes license plate letter by applying hybrid pattern vector method. Experimental results show that the proposed algorithm can recognize the front and rear direction license plate at real-time in the presence of complex background environments. Accordingly license plate detection rate displayed $98.8\%$ and $96.5\%$ successive rate respectively. And also, from the segmented letters, it shows $97.3\%$ and $96\%$ successive recognition rate respectively.

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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.

Reduction of Radiographic Quantum Noise Using Adaptive Weighted Median Filter (적응성 가중메디안 필터를 이용한 방사선 투과영상의 양자 잡음 제거)

  • Lee, Hoo-Min;Nam, Moon-Hyon
    • Journal of the Korean Society for Nondestructive Testing
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    • v.22 no.5
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    • pp.465-473
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    • 2002
  • Images are easily corrupted by noise during the data transmission, data capture and data processing. A technical method of noise analyzing and adaptive filtering for reducing of quantum noise in radiography is presented. By adjusting the characteristics of the filter according to local statistics around each pixel of the image as moving windowing, it is possible to suppress noise sufficiently while preserve edge and other significant information required in reading. We have proposed adaptive weighted median(AWM) filters based on local statistics. We show two ways of realizing the AWM filters. One is a simple type of AWM filter, whose weights are given by a simple non-linear function of three local characteristics. The other is the AWM filter which is constructed by homogeneous factor(HF). Homogeneous factor(HF) from the quantum noise models that enables the filter to recognize the local structures of the image is introduced, and an algorithm for determining the HF fitted to the detection systems with various inner statistical properties is proposed. We show by the experimented that the performances of proposed method is superior to these of other filters and models in preserving small details and suppressing the noise at homogeneous region. The proposed algorithms were implemented by visual C++ language on a IBM-PC Pentium 550 for testing purposes, the effects and results of the noise filtering were proposed by comparing with images of the other existing filtering methods.

Contour Extraction Method using p-Snake with Prototype Energy (원형에너지가 추가된 p-Snake를 이용한 윤곽선 추출 기법)

  • Oh, Seung-Taek;Jun, Byung-Hwan
    • Journal of the Institute of Electronics and Information Engineers
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    • v.51 no.4
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    • pp.101-109
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    • 2014
  • It is an essential element for the establishment of image processing related systems to find the exact contour from the image of an arbitrary object. In particular, if a vision system is established to inspect the products in the automated production process, it is very important to detect the contours for standardized shapes such lines and curves. In this paper, we propose a prototype adaptive dynamic contour model, p-Snake with improved contour extraction algorithms by adding the prototype energy. The proposed method is to find the initial contour by applying the existing Snake algorithm after Sobel operation is performed for prototype analysis. Next, the final contour of the object is detected by analyzing prototypes such as lines and circles, defining prototype energy and using it as an additional energy item in the existing Snake function on the basis of information on initial contour. We performed experiments on 340 images obtained by using an environment that duplicated the background of an industrial site. It was found that even if objects are not clearly distinguished from the background due to noise and lighting or the edges being insufficiently visible in the images, the contour can be extracted. In addition, in the case of similarity which is the measure representing how much it matches the prototype, the prototype similarity of contour extracted from the proposed p-ACM is superior to that of ACM by 9.85%.