Open AccessFlying small target detection in IR images based on adaptive toggle operator
Author(s) -
Marvasti Fereshteh Seyed,
Mosavi Mohammad Reza,
Nasiri Mahdi
Publication year - 2018
Publication title -
iet computer vision
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.38
H-Index - 37
eISSN - 1751-9640
pISSN - 1751-9632
DOI - 10.1049/iet-cvi.2017.0327
Subject(s) - clutter , artificial intelligence , computer vision , computer science , constant false alarm rate , pixel , contrast (vision) , tracking (education) , operator (biology) , pattern recognition (psychology) , target acquisition , image (mathematics) , object detection , radar , telecommunications , psychology , pedagogy , biochemistry , chemistry , repressor , transcription factor , gene
Automatic detection and tracking of a small target in infrared (IR) images are of great importance. Toggle operator (TO) is the newest class of non‐linear operator morphology that has been widely used in detection and tracking the target in IR images. The most important problem in improving the efficiency of the TO is to use structural elements (SEs) in accordance with signal‐to‐clutter ratio (SCR) of each image. Generally, the clutters and targets are different in case of each image; therefore, for images with different SCRs, using SEs with fixed pixels and dimensions cannot lead to successful target detection. In this study, a new method is presented based on genetic algorithm to achieve adaptive SE for target detection in IR images. In this method, by designing the SE in accordance with the characteristics of each image, a large amount of background clutter and noise is suppressed and the contrast between target and background is increased. The results of a large set of real IR images including moving targets show that the proposed algorithm is effective in target detection. In the proposed method, the contrast between the target and background clutter is greatly increased while maintaining a low false alarm rate.