IEICE TRANSACTIONS on Fundamentals
Context-Free Marker-Controlled Watershed Transform for Efficient Multi-Object Detection and Segmentation
Summary :
A high-speed context-free marker controlled and minima imposition-free watershed transform is proposed for efficient multi-object detection and segmentation from a complex background. The context-free markers are extracted from a complex backgrounded multi-object image using a noise tolerant attention operator. These make high speed marker-controlled watershed possible without over-segmentation and region merging. The proposed method presents a marker-constrained labeling that can speed up the segmentation of the marker-controlled watershed transform by eliminating the necessity of the minima imposition. Simulation results show that the proposed method can efficiently detect and segment multiple objects from a complex background while reducing the over-segmentation and computation time.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E84-A No.6 pp.1392-1400
- Publication Date
- 2001/06/01
- Publicized
- Online ISSN
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- Type of Manuscript
- Special Section PAPER (Special Section on Papers Selected from 2000 International Technical Conference on Circuits/Systems, Computers and Communications (ITC-CSCC 2000))
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Kyung-Seok SEO, Chang-Joon PARK, Sang-Hyun CHO, Heung-Moon CHOI, "Context-Free Marker-Controlled Watershed Transform for Efficient Multi-Object Detection and Segmentation" in IEICE TRANSACTIONS on Fundamentals,
vol. E84-A, no. 6, pp. 1392-1400, June 2001, doi: .
Abstract: A high-speed context-free marker controlled and minima imposition-free watershed transform is proposed for efficient multi-object detection and segmentation from a complex background. The context-free markers are extracted from a complex backgrounded multi-object image using a noise tolerant attention operator. These make high speed marker-controlled watershed possible without over-segmentation and region merging. The proposed method presents a marker-constrained labeling that can speed up the segmentation of the marker-controlled watershed transform by eliminating the necessity of the minima imposition. Simulation results show that the proposed method can efficiently detect and segment multiple objects from a complex background while reducing the over-segmentation and computation time.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e84-a_6_1392/_p
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@ARTICLE{e84-a_6_1392,
author={Kyung-Seok SEO, Chang-Joon PARK, Sang-Hyun CHO, Heung-Moon CHOI, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Context-Free Marker-Controlled Watershed Transform for Efficient Multi-Object Detection and Segmentation},
year={2001},
volume={E84-A},
number={6},
pages={1392-1400},
abstract={A high-speed context-free marker controlled and minima imposition-free watershed transform is proposed for efficient multi-object detection and segmentation from a complex background. The context-free markers are extracted from a complex backgrounded multi-object image using a noise tolerant attention operator. These make high speed marker-controlled watershed possible without over-segmentation and region merging. The proposed method presents a marker-constrained labeling that can speed up the segmentation of the marker-controlled watershed transform by eliminating the necessity of the minima imposition. Simulation results show that the proposed method can efficiently detect and segment multiple objects from a complex background while reducing the over-segmentation and computation time.},
keywords={},
doi={},
ISSN={},
month={June},}
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TY - JOUR
TI - Context-Free Marker-Controlled Watershed Transform for Efficient Multi-Object Detection and Segmentation
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1392
EP - 1400
AU - Kyung-Seok SEO
AU - Chang-Joon PARK
AU - Sang-Hyun CHO
AU - Heung-Moon CHOI
PY - 2001
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E84-A
IS - 6
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - June 2001
AB - A high-speed context-free marker controlled and minima imposition-free watershed transform is proposed for efficient multi-object detection and segmentation from a complex background. The context-free markers are extracted from a complex backgrounded multi-object image using a noise tolerant attention operator. These make high speed marker-controlled watershed possible without over-segmentation and region merging. The proposed method presents a marker-constrained labeling that can speed up the segmentation of the marker-controlled watershed transform by eliminating the necessity of the minima imposition. Simulation results show that the proposed method can efficiently detect and segment multiple objects from a complex background while reducing the over-segmentation and computation time.
ER -
English
