A new edge detection method for oil slick infrared aerial image

Yu Jing; Jubai An; Zhaoxia Liu; Jing Tian

doi:10.1117/12.921607

12 January 2012 A new edge detection method for oil slick infrared aerial image

Yu Jing, Jubai An, Zhaoxia Liu, Jing Tian

Proceedings Volume 8350, Fourth International Conference on Machine Vision (ICMV 2011): Computer Vision and Image Analysis; Pattern Recognition and Basic Technologies; 83501E (2012) https://doi.org/10.1117/12.921607
Event: Fourth International Conference on Machine Vision (ICMV 11), 2011, Singapore, Singapore

Abstract

Edge detection technology of oil spills image on the sea is one of most key technologies to monitor oil spills on the sea. This paper presents a new method to detect continuous and closed edges of oil slick infrared (IR) aerial images on the sea. The method is composed of two stages: determination of edge points and edge linking. Non-maximal suppression and self-adaptive dynamic block threshold (SADBT) algorithm are applied to determine edge points. Then an improved edge linking algorithm is used for linking discrete edge points into closed edge contours, according to a cost function of the combination of Euclidean distance, intensity and angle information of edge ending points to improve the edge linking decision. Using the proposed algorithm, we can gain continuous and closed edges of oil slick IR aerial images, thereby confirming the location and acreage of oil spill. The experiment results have shown that the proposed method improves the degree of automation of edge detection, suppresses the striping noise, intensity inhomogeneity and weak edge boundaries effectively.

Citation Download Citation

Yu Jing, Jubai An, Zhaoxia Liu, and Jing Tian "A new edge detection method for oil slick infrared aerial image", Proc. SPIE 8350, Fourth International Conference on Machine Vision (ICMV 2011): Computer Vision and Image Analysis; Pattern Recognition and Basic Technologies, 83501E (12 January 2012); https://doi.org/10.1117/12.921607

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