IEICE TRANSACTIONS on Information
Active Contour Using Local Regional Information on Extendable Search Lines (LRES) for Image Segmentation
Summary :
In this paper, we propose a novel active contour method for image segmentation using a local regional information on extendable search line. We call it the LRES active contour. Our active contour uses the intensity values along a set of search lines that are perpendicular to the contour front. These search lines are used to inform the contour front toward which direction to move in order to find the object's boundary. Unlike other methods, none of these search lines have a predetermined length. Instead, their length increases gradually until a boundary of the object is found. We compare the performance of our LRES active contour to other existing active contours, both edge-based and region-based. The results show that our method provides more desirable segmentation outcomes, particularly on some images where other methods may fail. Not only is our method robust to noise and able to reach into a deep concave shape, it also has a large capture range and performs well in segmenting heterogeneous textured objects.
- Publication
- IEICE TRANSACTIONS on Information Vol.E93-D No.6 pp.1625-1635
- Publication Date
- 2010/06/01
- Publicized
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.E93.D.1625
- Type of Manuscript
- PAPER
- Category
- Image Processing and Video Processing
Authors
Keyword
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Sopon PHUMEECHANYA, Charnchai PLUEMPITIWIRIYAWEJ, Saowapak THONGVIGITMANEE, "Active Contour Using Local Regional Information on Extendable Search Lines (LRES) for Image Segmentation" in IEICE TRANSACTIONS on Information,
vol. E93-D, no. 6, pp. 1625-1635, June 2010, doi: 10.1587/transinf.E93.D.1625.
Abstract: In this paper, we propose a novel active contour method for image segmentation using a local regional information on extendable search line. We call it the LRES active contour. Our active contour uses the intensity values along a set of search lines that are perpendicular to the contour front. These search lines are used to inform the contour front toward which direction to move in order to find the object's boundary. Unlike other methods, none of these search lines have a predetermined length. Instead, their length increases gradually until a boundary of the object is found. We compare the performance of our LRES active contour to other existing active contours, both edge-based and region-based. The results show that our method provides more desirable segmentation outcomes, particularly on some images where other methods may fail. Not only is our method robust to noise and able to reach into a deep concave shape, it also has a large capture range and performs well in segmenting heterogeneous textured objects.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.E93.D.1625/_p
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@ARTICLE{e93-d_6_1625,
author={Sopon PHUMEECHANYA, Charnchai PLUEMPITIWIRIYAWEJ, Saowapak THONGVIGITMANEE, },
journal={IEICE TRANSACTIONS on Information},
title={Active Contour Using Local Regional Information on Extendable Search Lines (LRES) for Image Segmentation},
year={2010},
volume={E93-D},
number={6},
pages={1625-1635},
abstract={In this paper, we propose a novel active contour method for image segmentation using a local regional information on extendable search line. We call it the LRES active contour. Our active contour uses the intensity values along a set of search lines that are perpendicular to the contour front. These search lines are used to inform the contour front toward which direction to move in order to find the object's boundary. Unlike other methods, none of these search lines have a predetermined length. Instead, their length increases gradually until a boundary of the object is found. We compare the performance of our LRES active contour to other existing active contours, both edge-based and region-based. The results show that our method provides more desirable segmentation outcomes, particularly on some images where other methods may fail. Not only is our method robust to noise and able to reach into a deep concave shape, it also has a large capture range and performs well in segmenting heterogeneous textured objects.},
keywords={},
doi={10.1587/transinf.E93.D.1625},
ISSN={1745-1361},
month={June},}
Copy
TY - JOUR
TI - Active Contour Using Local Regional Information on Extendable Search Lines (LRES) for Image Segmentation
T2 - IEICE TRANSACTIONS on Information
SP - 1625
EP - 1635
AU - Sopon PHUMEECHANYA
AU - Charnchai PLUEMPITIWIRIYAWEJ
AU - Saowapak THONGVIGITMANEE
PY - 2010
DO - 10.1587/transinf.E93.D.1625
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E93-D
IS - 6
JA - IEICE TRANSACTIONS on Information
Y1 - June 2010
AB - In this paper, we propose a novel active contour method for image segmentation using a local regional information on extendable search line. We call it the LRES active contour. Our active contour uses the intensity values along a set of search lines that are perpendicular to the contour front. These search lines are used to inform the contour front toward which direction to move in order to find the object's boundary. Unlike other methods, none of these search lines have a predetermined length. Instead, their length increases gradually until a boundary of the object is found. We compare the performance of our LRES active contour to other existing active contours, both edge-based and region-based. The results show that our method provides more desirable segmentation outcomes, particularly on some images where other methods may fail. Not only is our method robust to noise and able to reach into a deep concave shape, it also has a large capture range and performs well in segmenting heterogeneous textured objects.
ER -
English
