IEICE TRANSACTIONS on Information
Three-Level Broad-Edge Template Matching and Its Application to Real-Time Vision System
Summary :
This paper presents a new internal image representation, in which the scene is encoded into a three-intensity-level image. This representation is generated by Laplacian-Gaussian filtering followed by dual-thresholding. We refer to this imege as three-level broad-edge representation. It supresses the high frequency noise and shading in the image and encodes the sign of relative intensity of a pixel compared with surrounding region. Image model search based on cross correlation using this representation is as reliable as the one based on gray normalized correlation, while it reduces the computational cost by 50 times. We examined the reliability and realtime performance of this method when it is applied to an industrial object recognition task. Our prototype system achieves 32
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- IEICE TRANSACTIONS on Information Vol.E78-D No.12 pp.1526-1532
- Publication Date
- 1995/12/25
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- Online ISSN
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- Type of Manuscript
- Special Section PAPER (Special Issue on Machine Vision Applications)
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Kazuhiko SUMI, Manabu HASHIMOTO, Haruhisa OKUDA, Shin'ichi KURODA, "Three-Level Broad-Edge Template Matching and Its Application to Real-Time Vision System" in IEICE TRANSACTIONS on Information,
vol. E78-D, no. 12, pp. 1526-1532, December 1995, doi: .
Abstract: This paper presents a new internal image representation, in which the scene is encoded into a three-intensity-level image. This representation is generated by Laplacian-Gaussian filtering followed by dual-thresholding. We refer to this imege as three-level broad-edge representation. It supresses the high frequency noise and shading in the image and encodes the sign of relative intensity of a pixel compared with surrounding region. Image model search based on cross correlation using this representation is as reliable as the one based on gray normalized correlation, while it reduces the computational cost by 50 times. We examined the reliability and realtime performance of this method when it is applied to an industrial object recognition task. Our prototype system achieves 32
URL: https://global.ieice.org/en_transactions/information/10.1587/e78-d_12_1526/_p
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@ARTICLE{e78-d_12_1526,
author={Kazuhiko SUMI, Manabu HASHIMOTO, Haruhisa OKUDA, Shin'ichi KURODA, },
journal={IEICE TRANSACTIONS on Information},
title={Three-Level Broad-Edge Template Matching and Its Application to Real-Time Vision System},
year={1995},
volume={E78-D},
number={12},
pages={1526-1532},
abstract={This paper presents a new internal image representation, in which the scene is encoded into a three-intensity-level image. This representation is generated by Laplacian-Gaussian filtering followed by dual-thresholding. We refer to this imege as three-level broad-edge representation. It supresses the high frequency noise and shading in the image and encodes the sign of relative intensity of a pixel compared with surrounding region. Image model search based on cross correlation using this representation is as reliable as the one based on gray normalized correlation, while it reduces the computational cost by 50 times. We examined the reliability and realtime performance of this method when it is applied to an industrial object recognition task. Our prototype system achieves 32
keywords={},
doi={},
ISSN={},
month={December},}
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TY - JOUR
TI - Three-Level Broad-Edge Template Matching and Its Application to Real-Time Vision System
T2 - IEICE TRANSACTIONS on Information
SP - 1526
EP - 1532
AU - Kazuhiko SUMI
AU - Manabu HASHIMOTO
AU - Haruhisa OKUDA
AU - Shin'ichi KURODA
PY - 1995
DO -
JO - IEICE TRANSACTIONS on Information
SN -
VL - E78-D
IS - 12
JA - IEICE TRANSACTIONS on Information
Y1 - December 1995
AB - This paper presents a new internal image representation, in which the scene is encoded into a three-intensity-level image. This representation is generated by Laplacian-Gaussian filtering followed by dual-thresholding. We refer to this imege as three-level broad-edge representation. It supresses the high frequency noise and shading in the image and encodes the sign of relative intensity of a pixel compared with surrounding region. Image model search based on cross correlation using this representation is as reliable as the one based on gray normalized correlation, while it reduces the computational cost by 50 times. We examined the reliability and realtime performance of this method when it is applied to an industrial object recognition task. Our prototype system achieves 32
ER -
English
