Infrared image target detection process using continuous features

Minoru Kikuchi; Hiroyuki Tamura; Michinari Ono; Hiroshi Miyauchi; Shigenobu Kobayashi

doi:10.1117/12.395593

17 August 2000 Infrared image target detection process using continuous features

Minoru Kikuchi, Hiroyuki Tamura, Michinari Ono, Hiroshi Miyauchi, Shigenobu Kobayashi

Author Affiliations +

Proceedings Volume 4050, Automatic Target Recognition X; (2000) https://doi.org/10.1117/12.395593
Event: AeroSense 2000, 2000, Orlando, FL, United States

Abstract

In this paper, we discuss stability and accuracy of target detection process in infrared images, using continuous features of the target or target candidates, and we improve the accuracy of target detection by optimizing an evaluation function. This process carries out parallel image process. The one, Two-dimensional Constant False Alarm Rate (CFAR) process reduces background clatter. The other, Motion Vector Process detects moving target. In addition, Combined Target Detection Process improves the accuracy of target detection using features from two different processes. Continuous and stable data measurement is necessary to improve the accuracy of target detection. But measurement data have noises and fluctuations by change of the environment. In this case, we use continuous features to stable detection. On the other hand, optimizing weight vectors in evaluation function is necessary to improve target detection. But we have to deal with large number of parameters. In this optimization named Combined Target Detection Process, we use Genetic Algorithms (GA) to get a global optimum of parameters. This process is useful for outdoor surveillance systems, intelligent transport systems (ITS) and so on.

Citation Download Citation

Minoru Kikuchi, Hiroyuki Tamura, Michinari Ono, Hiroshi Miyauchi, and Shigenobu Kobayashi "Infrared image target detection process using continuous features", Proc. SPIE 4050, Automatic Target Recognition X, (17 August 2000); https://doi.org/10.1117/12.395593

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