Stochastic models for recognition of occluded targets

نویسندگان

  • Bir Bhanu
  • Yingqiang Lin
چکیده

Recognition of occluded objects in synthetic aperture radar (SAR) images is a signi0cant problem for automatic target recognition. Stochastic models provide some attractive features for pattern matching and recognition under partial occlusion and noise. In this paper, we present a hidden Markov modeling based approach for recognizing objects in SAR images. We identify the peculiar characteristics of SAR sensors and using these characteristics we develop feature based multiple models for a given SAR image of an object. The models exploiting the relative geometry of feature locations or the amplitude of SAR radar return are based on sequentialization of scattering centers extracted from SAR images. In order to improve performance we integrate these models synergistically using their probabilistic estimates for recognition of a particular target at a speci0c azimuth. Experimental results are presented using both synthetic and real SAR images. ? 2003 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

On Calibration and Application of Logit-Based Stochastic Traffic Assignment Models

There is a growing recognition that discrete choice models are capable of providing a more realistic picture of route choice behavior. In particular, influential factors other than travel time that are found to affect the choice of route trigger the application of random utility models in the route choice literature. This paper focuses on path-based, logit-type stochastic route choice models, i...

متن کامل

Recognition of Occluded Targets Using Stochastic Models

R ecognition of o cclude d obje cts in synthetic ap erture radar (SAR) images is a signi cant problem for automatic target recognition. In this paper, we present a hidden Markov modeling (HMM) based approach for recognizing objects in synthetic ap ertur eradar (SAR) images. We identify the peculiar char acteristics of SAR sensors and using these characteristics we develop featur ebased multiple...

متن کامل

A Chance Constrained Integer Programming Model for Open Pit Long-Term Production Planning

The mine production planning defines a sequence of block extraction to obtain the highest NPV under a number of constraints. Mathematical programming has become a widespread approach to optimize production planning, for open pit mines since the 1960s. However, the previous and existing models are found to be limited in their ability to explicitly incorporate the ore grade uncertainty into the p...

متن کامل

Recognition of Occluded Objects in SAR Images

Recognition of occluded objects in synthetic aperture radar SAR images is a signi cant problem for automatic target recognition Stochastic models provide some attractive features for pattern matching and recognition under partial occlusion and noise In this paper we present a discrete hidden Markov modeling HMM based approach for recognizing objects in synthetic aperture radar SAR images We ide...

متن کامل

Target Detection in Bistatic Passive Radars by Using Adaptive Processing Based on Correntropy Cost Function

In this paper a novel method is introduced for target detection in bistatic passive radars which uses the concept of correntropy to distinguish correct targets from false detections. In proposed method the history of each cell of ambiguity function is modeled as a stochastic process. Then the stochastic processes consist the noise are differentiated from those consisting targets by constructing...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • Pattern Recognition

دوره 36  شماره 

صفحات  -

تاریخ انتشار 2003