Abstract
A method named MACA was suggested. In the general Snake model, there is no required matching between orientation of the contour and edge direction in the grey-level image. This kind of Snake model may fail in the image with rich texture or with concave objects. To avoid it, two energy functions based on the above mentioned ideas were proposed to improve the Snake model. To reduce the time cost in the iteration of MACA, a fast Gready algorithm was proposed. Also, the first-order and second-order derivative, domain of searching area, contour resampling, and conditions of corner locking were redefined. Experimental results show that the proposed method is much better than the general Snake model, especially in searching for the concave objects.
| Original language | English |
|---|---|
| Pages (from-to) | 45-50 |
| Number of pages | 6 |
| Journal | Hongwai Yu Haomibo Xuebao/Journal of Infrared and Millimeter Waves |
| Volume | 16 |
| Issue number | 1 |
| Publication status | Published - 1997 Feb 1 |
| Externally published | Yes |
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ASJC Scopus subject areas
- Atomic and Molecular Physics, and Optics
Cite this
Modified active contour algorithm (MAXA) based on the edge direction information. / Shen, Dinggang; Qi, Feihu.
In: Hongwai Yu Haomibo Xuebao/Journal of Infrared and Millimeter Waves, Vol. 16, No. 1, 01.02.1997, p. 45-50.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Modified active contour algorithm (MAXA) based on the edge direction information
AU - Shen, Dinggang
AU - Qi, Feihu
PY - 1997/2/1
Y1 - 1997/2/1
N2 - A method named MACA was suggested. In the general Snake model, there is no required matching between orientation of the contour and edge direction in the grey-level image. This kind of Snake model may fail in the image with rich texture or with concave objects. To avoid it, two energy functions based on the above mentioned ideas were proposed to improve the Snake model. To reduce the time cost in the iteration of MACA, a fast Gready algorithm was proposed. Also, the first-order and second-order derivative, domain of searching area, contour resampling, and conditions of corner locking were redefined. Experimental results show that the proposed method is much better than the general Snake model, especially in searching for the concave objects.
AB - A method named MACA was suggested. In the general Snake model, there is no required matching between orientation of the contour and edge direction in the grey-level image. This kind of Snake model may fail in the image with rich texture or with concave objects. To avoid it, two energy functions based on the above mentioned ideas were proposed to improve the Snake model. To reduce the time cost in the iteration of MACA, a fast Gready algorithm was proposed. Also, the first-order and second-order derivative, domain of searching area, contour resampling, and conditions of corner locking were redefined. Experimental results show that the proposed method is much better than the general Snake model, especially in searching for the concave objects.
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M3 - Article
AN - SCOPUS:0031072246
VL - 16
SP - 45
EP - 50
JO - Hongwai Yu Haomibo Xuebao/Journal of Infrared and Millimeter Waves
JF - Hongwai Yu Haomibo Xuebao/Journal of Infrared and Millimeter Waves
SN - 1001-9014
IS - 1
ER -