Abstract
In this paper, we describe a new method for shape from focus using a set of the color segmentation and the bilateral filtering. The shape from focus estimates the geometrical shape of objects from the defocus level of images taken with different focal state. However, the conventional methods tend to fail in the shape estimation around the edge parts of objects and thin texture areas. To address the problems, we use the color segmentation in order to merge such areas by color, and then we interpolate the shape of lost part at each segment. The bilateral smoothing filter is used as the noise suppressor to improve the segmentation accuracy and also this bilateral filter is used to obtain the detail of textures, in other words, high frequency components of the focus measure. In addition, we also acquire the All-In-Focus image by this algorithm and the depth estimation is complemented by this image. By using this method, the lossless and noiseless shape of the object is obtained.
| Original language | English |
|---|---|
| Title of host publication | 2006 IEEE 12th Digital Signal Processing Workshop and 4th IEEE Signal Processing Education Workshop |
| Pages | 566-571 |
| Number of pages | 6 |
| DOIs | |
| Publication status | Published - 2006 |
| Event | 2006 IEEE 12th Digital Signal Processing Workshop and 4th IEEE Signal Processing Education Workshop, DSPWS - Moose, WY, United States Duration: 2006 Sep 24 → 2006 Sep 27 |
Other
| Other | 2006 IEEE 12th Digital Signal Processing Workshop and 4th IEEE Signal Processing Education Workshop, DSPWS |
|---|---|
| Country | United States |
| City | Moose, WY |
| Period | 06/9/24 → 06/9/27 |
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Keywords
- All-in-focus image
- Bilateral filter
- Color segmentation
- Focus measure
- Shape from focus
- Shape recovery
ASJC Scopus subject areas
- Signal Processing
- Electrical and Electronic Engineering
Cite this
Shape from focus using color segmentation and bilateral filter. / Shoji, H.; Shirai, K.; Ikehara, Masaaki.
2006 IEEE 12th Digital Signal Processing Workshop and 4th IEEE Signal Processing Education Workshop. 2006. p. 566-571 4041128.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Shape from focus using color segmentation and bilateral filter
AU - Shoji, H.
AU - Shirai, K.
AU - Ikehara, Masaaki
PY - 2006
Y1 - 2006
N2 - In this paper, we describe a new method for shape from focus using a set of the color segmentation and the bilateral filtering. The shape from focus estimates the geometrical shape of objects from the defocus level of images taken with different focal state. However, the conventional methods tend to fail in the shape estimation around the edge parts of objects and thin texture areas. To address the problems, we use the color segmentation in order to merge such areas by color, and then we interpolate the shape of lost part at each segment. The bilateral smoothing filter is used as the noise suppressor to improve the segmentation accuracy and also this bilateral filter is used to obtain the detail of textures, in other words, high frequency components of the focus measure. In addition, we also acquire the All-In-Focus image by this algorithm and the depth estimation is complemented by this image. By using this method, the lossless and noiseless shape of the object is obtained.
AB - In this paper, we describe a new method for shape from focus using a set of the color segmentation and the bilateral filtering. The shape from focus estimates the geometrical shape of objects from the defocus level of images taken with different focal state. However, the conventional methods tend to fail in the shape estimation around the edge parts of objects and thin texture areas. To address the problems, we use the color segmentation in order to merge such areas by color, and then we interpolate the shape of lost part at each segment. The bilateral smoothing filter is used as the noise suppressor to improve the segmentation accuracy and also this bilateral filter is used to obtain the detail of textures, in other words, high frequency components of the focus measure. In addition, we also acquire the All-In-Focus image by this algorithm and the depth estimation is complemented by this image. By using this method, the lossless and noiseless shape of the object is obtained.
KW - All-in-focus image
KW - Bilateral filter
KW - Color segmentation
KW - Focus measure
KW - Shape from focus
KW - Shape recovery
UR - http://www.scopus.com/inward/record.url?scp=39049153930&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=39049153930&partnerID=8YFLogxK
U2 - 10.1109/DSPWS.2006.265487
DO - 10.1109/DSPWS.2006.265487
M3 - Conference contribution
AN - SCOPUS:39049153930
SP - 566
EP - 571
BT - 2006 IEEE 12th Digital Signal Processing Workshop and 4th IEEE Signal Processing Education Workshop
ER -