Share Email Print

Proceedings Paper

Infrared object recognition based on multiple features by integrated neural networks
Author(s): Huilin Jiang; Huamin Yang; Zhengang Jiang
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

Because ofthe inherent features ofdetectors, the lower contrast between object and background, ambiguous image edge and great noise have widely existed in the infrared image. It's hard to get the better result by the general method when detecting and recognizing infrared images. The recognition method for infrared objects based on multiple features by integrated neural networks, which is proposed in this paper, not only has improved the reliability, but avoided the system halting because ofthe invalidity on some feature. This paper describes and implements this method from the following aspects: infrared object image processing, image segmentation, feature abstraction, and object recognition by integrated neural networks. According the experience, the image preprocessing has improved image signal noise ratio by close frame accumulation, and smoothing and decreasing noise based on the space variant scale in deformable model has guaranteed the nicer edge effect and established the good foundation for the further image segmentation. Image segmentation and feature abstraction are important steps in the course of image recognition. Segment the object image by the integrated consideration of difference operators and histogram switch, then abstract the features from it, we can find ten aspects relating to the infrared image feature and object. Finally, it fulfils information fusion by processing abstract object features with integrated neural networks, realizes the infrared object recognition, and avoids the whole system halting when some feature information is lost.

Paper Details

Date Published: 30 August 2002
PDF: 5 pages
Proc. SPIE 4925, Electronic Imaging and Multimedia Technology III, (30 August 2002); doi: 10.1117/12.481614
Show Author Affiliations
Huilin Jiang, Changchun Univ. of Science and Technology (China)
Huamin Yang, Changchun Univ. of Science and Technology (China)
Zhengang Jiang, Changchun Univ. of Science and Technology (China)

Published in SPIE Proceedings Vol. 4925:
Electronic Imaging and Multimedia Technology III
LiWei Zhou; Chung-Sheng Li; Yoshiji Suzuki, Editor(s)

© SPIE. Terms of Use
Back to Top