Segmenting images with support vector machines

被引：0

作者：

Reyna, RA ^{[1
]}

Hernandez, N ^{[1
]}

Esteve, D ^{[1
]}

Cattoen, M ^{[1
]}

机构：

[1] CNRS, LAAS, F-31077 Toulouse, France

来源：

2000 INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, VOL I, PROCEEDINGS | 2000年

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The aim of this work is to propose an original image segmentation methodology to detect and localise objects or patterns in an image. This new technology has two parts: a) the main module is a SVM Neural Network whose goal is the image segmentation in order to detect and localise objects having regular patterns represented by a block of pixels, and then, b) a simple morphological processing, to eliminate isolated misclassified pixels. The importance of this new methodology is highlighted with the results obtained in the recognition of 2D symbolic codes. Another advantage of our algorithm is its regularity that may be exploited to propose a parallel hardware architecture.

引用

页码：820 / 823

页数：4

共 50 条

[41] Support vector machines for classification of hyperspectral remote-sensing images
Melgani, F
Bruzzone, L
IGARSS 2002: IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM AND 24TH CANADIAN SYMPOSIUM ON REMOTE SENSING, VOLS I-VI, PROCEEDINGS: REMOTE SENSING: INTEGRATING OUR VIEW OF THE PLANET, 2002, : 506 - 508
[42] Obscure bleeding detection in endoscopy images using support vector machines
Jianguo Liu
Xiaohui Yuan
Optimization and Engineering, 2009, 10 : 289 - 299
[43] One-class support vector machines for aerial images segmentation
Wu, Chih-Hung
Lai, Chih-Chin
Chen, Chun-Yen
Chen, Yan-He
World Academy of Science, Engineering and Technology, 2010, 65 : 881 - 886
[44] Support Vector Machines for road extraction from remotely sensed images
Yager, N
Sowmya, A
COMPUTER ANALYSIS OF IMAGES AND PATTERNS, PROCEEDINGS, 2003, 2756 : 285 - 292
[45] I semantic extraction of the building images using support vector machines
Wang, YN
Chen, LB
Hu, BG
2002 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-4, PROCEEDINGS, 2002, : 1608 - 1613
[46] Enhancement of the Classification of Multichannel Chromosome Images Using Support Vector Machines
Karvelis, P. S.
Fotiadis, D. I.
Georgiou, I.
Sakaloglou, P.
2009 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-20, 2009, : 3601 - 3604
[47] Classification of hyperspectral endocrine tissue images using support vector machines
Maktabi, Marianne
Koehler, Hannes
Ivanova, Magarita
Neumuth, Thomas
Rayes, Nada
Seidemann, Lena
Sucher, Robert
Jansen-Winkeln, Boris
Gockel, Ines
Barberio, Manuel
Chalopin, Claire
INTERNATIONAL JOURNAL OF MEDICAL ROBOTICS AND COMPUTER ASSISTED SURGERY, 2020, 16 (05): : 1 - 10
[48] Human Detection in Images via Piecewise Linear Support Vector Machines
Ye, Qixiang
Han, Zhenjun
Jiao, Jianbin
Liu, Jianzhuang
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2013, 22 (02) : 778 - 789
[49] ABNORMALITY DETECTION FOR CAPSULE ENDOSCOPE IMAGES BASED ON SUPPORT VECTOR MACHINES
Timotius, Ivanna K.
Miaou, Shaou-Gang
Valdeavilla, Edreen Bryan
Liu, Yi-Hung
BIOMEDICAL ENGINEERING-APPLICATIONS BASIS COMMUNICATIONS, 2012, 24 (01): : 71 - 83
[50] Automated detection of pulmonary nodules in CT images with support vector machines
Liu Lu
Liu Wanyu
Sun Xiaoming
FIFTH INTERNATIONAL SYMPOSIUM ON INSTRUMENTATION SCIENCE AND TECHNOLOGY, 2009, 7133

← 1 2 3 4 5 →