• Title/Summary/Keyword: Edge Map

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Inverse halftoning Using Anisotropic diffusion and Edge map (비등방성 확산 필터와 에지맵을 이용한 역하프토닝)

  • 고기영;주동현;염동훈;김두영
    • Proceedings of the Korea Institute of Convergence Signal Processing
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    • 2000.12a
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    • pp.81-84
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    • 2000
  • Digital Halftoning convert a continuous-tone images to a binary images. Inverse halftoning addresses the problem of recovering a continuous image from a halftoned binary image. Simple low pass filtering can remove the high frequency noise but it also removes the edge information. Thus the edge information should be separated from the halftoning noise. As a result, the edge of result image is blurring. This paper present that we obtain continuous-tone-image which using Anisotropic diffusion filter. To reduce noise without blurring the edges of reconstructed image use edge map. The experimental results show that proposed method gives a higher PSNR and better subjective quality than conventional methods. As a result, the edge information of reconstructed image reduce blurring.

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A Study on the Depth Map using Single Edge (단일 엣지를 이용한 깊이 정보에 관한 연구)

  • Kim, Young-Seop;Song, Eung-Yeol
    • Journal of the Semiconductor & Display Technology
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    • v.9 no.2
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    • pp.123-126
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    • 2010
  • An implementation of modified stereo matching using efficient belief propagation (BP) algorithm is presented in this paper. We do recommend the use of the simple sobel, prewitt edge operator. The application of B band sobel edge operator over image demonstrates result with somewhat noisy (distinct border). When we adopt the only MRF + BP algorithm, however, borders cannot be distinguished due to that the message functions in the BP algorithm is just the mechanism which passes energy data to the only large gap of each Message functions In order to address the abovementioned disadvantageous phenomenon, we use the sobel edge operator + MRF + BP algorithm to distinguish the border that is located between the similar message data. Using edge information, the result shows that our proposed process diminishes the propagation of wrong probabilistic information. The enhanced result is due to that our proposed method effectively reduced errors incurred by ambiguous scene properties.

Object Detection Algorithm in Sea Environment Based on Frequency Domain (주파수 도메인에 기반한 해양 물표 검출 알고리즘)

  • Park, Ki-Tae;Jeong, Jong-Myeon
    • Journal of the Korean Institute of Intelligent Systems
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    • v.22 no.4
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    • pp.494-499
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    • 2012
  • In this paper, a new method for detecting various objects that can be risks to safety navigation in sea environment is proposed. By analysing Infrared(IR) images obtained from various sea environments, we could find out that object regions include both horizontal and vertical direction edges while background regions of sea surface mainly include vertical direction edges. Therefore, we present an approach to detecting object regions considering horizontal and vertical edges. To this end, in the first step, image enhancement is performed by suppressing noises such as sea glint and complex clutters using a statistical filter. In the second step, a horizontal edge map and a vertical edge map are generated by 1-D Discrete Cosine Transform technique. Then, a combined map integrating the horizontal and the vertical edge maps is generated. In the third step, candidate object regions are detected by a adaptive thresholding method. Finally, exact object regions are extracted by eliminating background and clutter regions based on morphological operation.

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 Contour-Preserving Image Filtering for Noise Removal (잡음 제거를 위한 윤곽선 보존 기법에 관한 연구)

  • Yoo, Choong-Woong;Ryu, Dae-Hyun;Bae, Kang-Yeul
    • Journal of the Korean Institute of Telematics and Electronics T
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    • v.36T no.4
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    • pp.24-29
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    • 1999
  • In this paper, a simple contour-preserving filtering algorithm is proposed. The goal of the contour-preserving filtering method is to remove noise ad granularity as the preprocessing for the image segmentation procedure. Our method finds edge map and separates the image into the edge region and the non-edge region using this edge map. For the non-edge region, typical smoothing filters could be used to remove the noise and the small areas during the segmentation procedure. The result of simulation shows that our method is slightly better than the typical methods such as the median filtering and gradient inverse weighted filtering in the point of view of analysis of variance (ANOVA).

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Stereo Matching Based on Edge and Area Information (경계선 및 영역 정보를 이용한 스테레오 정합)

  • 한규필;김용석;하경훈;하영호
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.32B no.12
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    • pp.1591-1602
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    • 1995
  • A hybrid approach which includes edge- and region-based methods is considered. The modified non-linear Laplacian(MNL) filter is used for feature extraction. The matching algorithm has three steps which are edge, signed region, and residual region matching. At first, the edge points are matched using the sign and direction of edges. Then, the disparity is propagated from edge to inside region. A variable window is used to consider the local method which give accurate matched points and area-based method which can obtain full-resolution disparity map. In addition, a new relaxation algorithm for considering matching possibility derived from normalized error and regional continuity constraint is proposed to reduce the mismatched points. By the result of simulation for various images, this algorithm is insensitive to noise and gives full- resolution disparity map.

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An Efficient Representation of Edge Shapes in Topological Maps

  • Doh, Nakju Lett;Chung, Wan-Kyun
    • ETRI Journal
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    • v.29 no.5
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    • pp.655-666
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    • 2007
  • There are nodes and edges in a topological map. Node data has been used as a main source of information for the localization of mobile robots. In contrast, edge data is regarded as a minor source of information, and it has been used in an intuitive and heuristic way. However, edge data also can be used as a good source of information and provide a way to use edge data efficiently. For that purpose, we define a data format which describes the shape of an edge. This format is called local generalized Voronoi graph's angle (LGA). However, the LGA is constituted of too many samples; therefore, real time localization cannot be performed. To reduce the number of samples, we propose a compression method which utilizes wavelet transformation. This method abstracts the LGA by key factors using far fewer samples than the LGA. Experiments show that the LGA accurately describes the shape of the edges and that the key factors preserve most information of the LGA while reducing the number of samples.

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Image Compression Using Edge Map And Multi-Sided Side Match Finite-State Vector Quantization (윤곽선 맵과 다중 면 사이드 매치 유한상태 벡터 양자화를 이용한 영상 압축)

  • Cho, Seong-Hwan;Kim, Eung-Sung
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.8 no.6
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    • pp.1419-1427
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    • 2007
  • In this paper, we propose an algorithm which implements a multi-sided side match finite-state vector quantization(MSMVQ). After extracting the edge information from an image and classifying the image into edge blocks or non-edge blocks, we construct an edge map. We subdivide edge blocks into sixteen classes using discrete cosine transform(DCT) AC coefficients. Based on edge map information, a state codebook is made from the master codebook, and side match calculation is done for two-sided or three-sided current block of image. For reducing transmitted bits, a decision is made whether or not to encode the non-edge blocks among the pre-coded blocks by using the master codebook. Also for reducing allocation bits of codeword indices to decoder, a variable length coder is used. Considering the comparison with side match finite-state vector quantization(SMVQ) and two-sided SMVQ(TSMVQ) algorithm about Zelda, Lenna, Bridge and Peppers image, the new algorithm shows better picture quality than SMVQ and TSMVQ respectively.

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An Improved Level Set Method to Image Segmentation Based on Saliency

  • Wang, Yan;Xu, Xianfa
    • Journal of Information Processing Systems
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    • v.15 no.1
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    • pp.7-21
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    • 2019
  • In order to improve the edge segmentation effect of the level set image segmentation and avoid the influence of the initial contour on the level set method, a saliency level set image segmentation model based on local Renyi entropy is proposed. Firstly, the saliency map of the original image is extracted by using saliency detection algorithm. And the outline of the saliency map can be used to initialize the level set. Secondly, the local energy and edge energy of the image are obtained by using local Renyi entropy and Canny operator respectively. At the same time, new adaptive weight coefficient and boundary indication function are constructed. Finally, the local binary fitting energy model (LBF) as an external energy term is introduced. In this paper, the contrast experiments are implemented in different image database. The robustness of the proposed model for segmentation of images with intensity inhomogeneity and complicated edges is verified.

An Edge Detector by Using Perfect Sharpening of Ramps (램프의 완전 선명화를 이용한 에지 검출기)

  • Lee, Jong-Gu;Yoo, Cheol-Jung;Chang, Ok-Bae
    • Journal of KIISE:Software and Applications
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    • v.34 no.11
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    • pp.961-970
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    • 2007
  • Since the usual conventional edge detectors employ the local differential derivatives, the detected edges are not uniform in their widths or some edges are missed out of the detection on magnified images. We employ a mapping from the exactly monotonic intensity distributions of ramp edges to the simple step functions of intensity, which is referred to as perfect sharpening map of ramp edges. This map is based on the non-local feature of intensity distribution and used to introduce a modified differentiation, in terms of which we can construct an efficient edge detector adaptive to the variation of edge width. By adopting the operator MADD in this paper, we developed an edge detector that works stably against the magnification of image or the variation of edge width. It is shown by comparing to the conventional algorithms that the proposed one is very excellent.