• Title/Summary/Keyword: Edge extraction and complement

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Text Extraction Algorithm in Complex Images using Adaptive Edge detection (복잡한 영상에서 적응적 에지검출을 이용한 텍스트 추출 알고리즘 연구)

  • Shin, Seong;Kim, Sung-Dong;Baek, Young-Hyun;Moon, Sung-Ryong
    • Proceedings of the IEEK Conference
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    • 2007.07a
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    • pp.251-252
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    • 2007
  • The thesis proposed the Text Extraction Algorithm which is a text extraction algorithm which uses the Coiflet Wavelet, YCbCr Color model and the close curve edge feature of adaptive LoG Operator in order to complement the demerit of the existing research which is weak in complexity of background, variety of light and disordered line and similarity of text and background color. This thesis is simulated with natural images which include naturally text area regardless of size, resolution and slant and so on of image. And the proposed algorithm is confirmed to an excellent by compared with an existing extraction algorithm in same image.

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Extraction and Complement of Hexagonal Borders in Corneal Endothelial Cell Images (각막 내피 세포 영상내 육각형 경계의 검출과 보완법)

  • Kim, Eung-Kyeu
    • Journal of the Institute of Electronics and Information Engineers
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    • v.50 no.3
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    • pp.102-112
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    • 2013
  • In this paper, two step processing method of contour extraction and complement which contain hexagonal shape for low contrast and noisy images is proposed. This method is based on the combination of Laplacian-Gaussian filter and an idea of filters which are dependent on the shape. At the first step, an algorithm which has six masks as its extractors to extract the hexagonal edges especially in the corners is used. Here, two tricorn filters are used to detect the tricorn joints of hexagons and other four masks are used to enhance the line segments of hexagonal edges. As a natural image, a corneal endothelial cell image which usually has regular hexagonal form is selected. The edge extraction of hexagonal shapes in corneal endothelial cell is important for clinical diagnosis. The proposed algorithm and other conventional methods are applied to noisy hexagonal images to evaluate each efficiency. As a result, this proposed algorithm shows a robustness against noises and better detection ability in the aspects of the output signal to noise ratio, the edge coincidence ratio and the extraction accuracy factor as compared with other conventional methods. At the second step, the lacking part of the thinned image by an energy minimum algorithm is complemented, and then the area and distribution of cells which give necessary information for medical diagnosis are computed.