Sketch-Based Evaluation of Image Segmentation Methods
Summary :
A method for evaluating image segmentation methods is proposed in this paper. The method is based on a perception model where the drawing act is used to represent visual mental percepts. Each segmented image is represented by a minimal set of features and the segmentation method is tested against a set of sketches that represent a subset of the original image database, using the Mahalanobis distance function. The covariance matrix is set using a collection of sketches drawn by different users. The different drawings are demonstrated to be consistent across users. This evaluation method can be used to solve the problem of parameter selection in image segmentation, as well as to show the goodness or limitations of the different segmentation algorithms. Different well-known color segmentation algorithms are analyzed with the proposed method and the nature of each one is discussed. This evaluation method is also compared with heuristic functions that serve for the same purpose, showing the importance of using users' pictorial knowledge.
- Publication
- IEICE TRANSACTIONS on Information Vol.E90-D No.1 pp.156-164
- Publication Date
- 2007/01/01
- Publicized
- Online ISSN
- 1745-1361
- DOI
- Type of Manuscript
- Special Section PAPER (Special Section on Advanced Image Technology)
- Category
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David GAVILAN, Hiroki TAKAHASHI, Suguru SAITO, Masayuki NAKAJIMA, "Sketch-Based Evaluation of Image Segmentation Methods" in IEICE TRANSACTIONS on Information,
vol. E90-D, no. 1, pp. 156-164, January 2007, doi: .
Abstract: A method for evaluating image segmentation methods is proposed in this paper. The method is based on a perception model where the drawing act is used to represent visual mental percepts. Each segmented image is represented by a minimal set of features and the segmentation method is tested against a set of sketches that represent a subset of the original image database, using the Mahalanobis distance function. The covariance matrix is set using a collection of sketches drawn by different users. The different drawings are demonstrated to be consistent across users. This evaluation method can be used to solve the problem of parameter selection in image segmentation, as well as to show the goodness or limitations of the different segmentation algorithms. Different well-known color segmentation algorithms are analyzed with the proposed method and the nature of each one is discussed. This evaluation method is also compared with heuristic functions that serve for the same purpose, showing the importance of using users' pictorial knowledge.
URL: https://global.ieice.org/en_transactions/information/10.1587/e90-d_1_156/_p
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@ARTICLE{e90-d_1_156,
author={David GAVILAN, Hiroki TAKAHASHI, Suguru SAITO, Masayuki NAKAJIMA, },
journal={IEICE TRANSACTIONS on Information},
title={Sketch-Based Evaluation of Image Segmentation Methods},
year={2007},
volume={E90-D},
number={1},
pages={156-164},
abstract={A method for evaluating image segmentation methods is proposed in this paper. The method is based on a perception model where the drawing act is used to represent visual mental percepts. Each segmented image is represented by a minimal set of features and the segmentation method is tested against a set of sketches that represent a subset of the original image database, using the Mahalanobis distance function. The covariance matrix is set using a collection of sketches drawn by different users. The different drawings are demonstrated to be consistent across users. This evaluation method can be used to solve the problem of parameter selection in image segmentation, as well as to show the goodness or limitations of the different segmentation algorithms. Different well-known color segmentation algorithms are analyzed with the proposed method and the nature of each one is discussed. This evaluation method is also compared with heuristic functions that serve for the same purpose, showing the importance of using users' pictorial knowledge.},
keywords={},
doi={},
ISSN={1745-1361},
month={January},}
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TY - JOUR
TI - Sketch-Based Evaluation of Image Segmentation Methods
T2 - IEICE TRANSACTIONS on Information
SP - 156
EP - 164
AU - David GAVILAN
AU - Hiroki TAKAHASHI
AU - Suguru SAITO
AU - Masayuki NAKAJIMA
PY - 2007
DO -
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E90-D
IS - 1
JA - IEICE TRANSACTIONS on Information
Y1 - January 2007
AB - A method for evaluating image segmentation methods is proposed in this paper. The method is based on a perception model where the drawing act is used to represent visual mental percepts. Each segmented image is represented by a minimal set of features and the segmentation method is tested against a set of sketches that represent a subset of the original image database, using the Mahalanobis distance function. The covariance matrix is set using a collection of sketches drawn by different users. The different drawings are demonstrated to be consistent across users. This evaluation method can be used to solve the problem of parameter selection in image segmentation, as well as to show the goodness or limitations of the different segmentation algorithms. Different well-known color segmentation algorithms are analyzed with the proposed method and the nature of each one is discussed. This evaluation method is also compared with heuristic functions that serve for the same purpose, showing the importance of using users' pictorial knowledge.
ER -
English
