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Article Navigation >  Journal of University of Electronic Science and Technology of China  > 2007  >  36(6): 1308-1310

CHEN Yu-bo, XU Hai-zhu, HUANG Ting-ting, ZHU Jian-jun. Determine Mouth Position in Face Image[J]. Journal of University of Electronic Science and Technology of China, 2007, 36(6): 1308-1310.
Citation: CHEN Yu-bo, XU Hai-zhu, HUANG Ting-ting, ZHU Jian-jun. Determine Mouth Position in Face Image[J]. Journal of University of Electronic Science and Technology of China, 2007, 36(6): 1308-1310.
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Determine Mouth Position in Face Image

  • 1.

    School of Info-Physics and Geomatics Engineering Central South University Changsha 410083;

  • 2.

    School of Information Science and Engineering,Central South University Changsha 410083

  • Received Date: 2007-07-10
  • Publish Date: 2007-12-15
  • The iterative threshold choosing algorithm is used to changes the gray image into binary image in the low half of a known face image, the area of mouth and nose can be obtained without manual work. This algorithm improves the traditional method limitation, such as vague mouth contour and poor connection quality. The erosion and dilation arithmetic is used to delete the minor noise area; the minimum enclosing rectangle is used to describe the shape of every area; and the mouth area is determined according to the prior knowledge of the mouth shape and size. The mouth center is represented by the centroid of the mouth connection area. Harris corner detection arithmetic is used to detect the two corners of the mouth in the mouth area of the original gray image. Experiment shows that the algorithm presented in this paper is quicker and more accurate than traditional methods.
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  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

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Determine Mouth Position in Face Image

  • 1. School of Info-Physics and Geomatics Engineering Central South University Changsha 410083;
  • 2. School of Information Science and Engineering,Central South University Changsha 410083
  • Received Date: 2007-07-10
  • Publish Date: 2007-12-15

Abstract: The iterative threshold choosing algorithm is used to changes the gray image into binary image in the low half of a known face image, the area of mouth and nose can be obtained without manual work. This algorithm improves the traditional method limitation, such as vague mouth contour and poor connection quality. The erosion and dilation arithmetic is used to delete the minor noise area; the minimum enclosing rectangle is used to describe the shape of every area; and the mouth area is determined according to the prior knowledge of the mouth shape and size. The mouth center is represented by the centroid of the mouth connection area. Harris corner detection arithmetic is used to detect the two corners of the mouth in the mouth area of the original gray image. Experiment shows that the algorithm presented in this paper is quicker and more accurate than traditional methods.

CHEN Yu-bo, XU Hai-zhu, HUANG Ting-ting, ZHU Jian-jun. Determine Mouth Position in Face Image[J]. Journal of University of Electronic Science and Technology of China, 2007, 36(6): 1308-1310.
Citation: CHEN Yu-bo, XU Hai-zhu, HUANG Ting-ting, ZHU Jian-jun. Determine Mouth Position in Face Image[J]. Journal of University of Electronic Science and Technology of China, 2007, 36(6): 1308-1310.
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