Mine boundary detection using partially ordered Markov models

Xia Hua; Jennifer L. Davidson; Noel A. C. Cressie

doi:10.1117/12.279638

14 October 1997 Mine boundary detection using partially ordered Markov models

Xia Hua, Jennifer L. Davidson, Noel A. C. Cressie

Proceedings Volume 3167, Statistical and Stochastic Methods in Image Processing II; (1997) https://doi.org/10.1117/12.279638
Event: Optical Science, Engineering and Instrumentation '97, 1997, San Diego, CA, United States

Abstract

Detection of objects in images in an automated fashion is necessary for many applications, including automated target recognition. In this paper, we present results of an automated boundary detection procedure using a new subclass of Markov random fields (MRFs), called partially ordered Markov models (POMMs). POMMs offer computational advantages over general MRFs. We show how a POMM can model the boundaries in an image. Our algorithm for boundary detection uses a Bayesian approach to build a posterior boundary model that locates edges of objects having a closed-loop boundary. We apply our method to images of mines with very good results.

Citation Download Citation

Xia Hua, Jennifer L. Davidson, and Noel A. C. Cressie "Mine boundary detection using partially ordered Markov models", Proc. SPIE 3167, Statistical and Stochastic Methods in Image Processing II, (14 October 1997); https://doi.org/10.1117/12.279638

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