Unsupervised evaluation of image segmentation application to multi-spectral images

被引：39

作者：

Chabrier, S ^{[1
]}

Emile, B ^{[1
]}

Laurent, H ^{[1
]}

Rosenberger, C ^{[1
]}

Marché, P ^{[1
]}

机构：

[1] Univ Orleans, ENSI Bourges, UPRES EA 2078, Lab Vis & Robot, F-18020 Bourges, France

来源：

PROCEEDINGS OF THE 17TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOL 1 | 2004年

关键词：

D O I：

10.1109/ICPR.2004.1334206

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We present in this article a study of some unsupervised evaluation criteria of an image segmentation result. The goal of this work is to be able to automatically choose the parameters of a segmentation method best fitted for an image or to fusion different segmentation results. We compared six unsupervised evaluation criteria on a database composed of 100 synthetic gray-level images segmented by four methods. Vinet's measure is used as an objective function to compare the behavior of the different criteria. We finally apply these criteria to evaluate segmentation results of multi-components images. We present in this article some experimental results of evaluation of gray-level and multicomponents natural images.

引用

页码：576 / 579

页数：4

共 10 条

[1]

BARRA V, 2000, THESIS U AUVERGNE

[2] Quantitative evaluation of color image segmentation results [J].

Borsotti, M ;

Campadelli, P ;

Schettini, R .

PATTERN RECOGNITION LETTERS, 1998, 19 (08) :741-747

[3]

Brodatz P, 1966, TEXTURES PHOTOGRAPHI

[4] Mean shift: A robust approach toward feature space analysis [J].

Comaniciu, D ;

Meer, P .

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2002, 24 (05) :603-619

[5]

MCCANE B, 1997, EVALUATION IMAGE SEG

[6] LOW-LEVEL IMAGE SEGMENTATION - AN EXPERT SYSTEM [J].

NAZIF, AM ;

LEVINE, MD .

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 1984, 6 (05) :555-577

[7]

Paras S, 1999, SUSTAIN DEV, V7, P1

[8]

Rosenberger C, 2000, INT CONF ACOUST SPEE, P2223, DOI 10.1109/ICASSP.2000.859280

[9]

ROSENBERGER C, 2003, INT C ADV CONC INT V

[10] A survey on evaluation methods for image segmentation [J].

Zhang, YJ .

PATTERN RECOGNITION, 1996, 29 (08) :1335-1346

← 1 →