Hybrid road recognition method using fuzzy c-means and back-propagation neural network and image processing

Chaofeng Li; Maolong Yang; Chengxian Shi; Deshen Xia

doi:10.1117/12.539027

25 September 2003 Hybrid road recognition method using fuzzy c-means and back-propagation neural network and image processing

Chaofeng Li, Maolong Yang, Chengxian Shi, Deshen Xia

Author Affiliations +

Proceedings Volume 5286, Third International Symposium on Multispectral Image Processing and Pattern Recognition; (2003) https://doi.org/10.1117/12.539027
Event: Third International Symposium on Multispectral Image Processing and Pattern Recognition, 2003, Beijing, China

Abstract

Road extracted from satellite imagery have been used for many different purposes, e.g. military, map publishing, transportation, and car navigations, etc. Many method such as, neural network, Knowledge-based, Optimal search, Snake model, Semantic model, Road operator model, etc. was researched to identify road from satellite image, but because of complicated characteristics of road and image itself, and automated road network extraction still remains a challenge problem, and no existing software is able to perform the task reliably. This paper presents a hybrid method which combines Fuzzy-C-Means with back-propagation neural network and knowledge processing technique to detect roads in SPOT image. The basic idea of the paper is "easiest first" principal, and firstly focus to extract local salient road segments most easily and reliably, then use contextual knowledge and supervised back-propagation neural network model to extract fuzzy road segments among salient road segment, and then grouping these extracted pixel as seed point, candidate point, and not-road point, and then according to appropriate knowledge rule to traversal and join, guide the further road link in the whole image. At last, some post-processing steps are taken to refine the result. The resultant image shows this hybrid identification method performs better than only using knowledge-based method or neural network techniques.

Citation Download Citation

Chaofeng Li, Maolong Yang, Chengxian Shi, and Deshen Xia "Hybrid road recognition method using fuzzy c-means and back-propagation neural network and image processing", Proc. SPIE 5286, Third International Symposium on Multispectral Image Processing and Pattern Recognition, (25 September 2003); https://doi.org/10.1117/12.539027

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
5 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Roads

Image segmentation

Neural networks

Image processing

Fuzzy logic

Earth observing sensors

Satellite imaging

Show All Keywords

Keywords/Phrases

Search In:

Publication Years