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Infrared Small Moving Target Detection via Saliency Histogram and Geometrical Invariability

Authors :
Minjie Wan
Kan Ren
Guohua Gu
Xiaomin Zhang
Weixian Qian
Qian Chen
Shuai Yu
Source :
Applied Sciences, Vol 7, Iss 6, p 569 (2017)
Publication Year :
2017
Publisher :
MDPI AG, 2017.

Abstract

In order to detect both bright and dark small moving targets effectively in infrared (IR) video sequences, a saliency histogram and geometrical invariability based method is presented in this paper. First, a saliency map that roughly highlights the salient regions of the original image is obtained by tuning its amplitude spectrum in the frequency domain. Then, a saliency histogram is constructed by means of averaging the accumulated saliency value of each gray level in the map, through which bins corresponding to bright target and dark target are assigned with large values in the histogram. Next, single-frame detection of candidate targets is accomplished by a binarized segmentation using an adaptive threshold, and their centroid coordinates with sub-pixel accuracy are calculated through a connected components labeling method as well as a gray-weighted criterion. Finally, considering the motion characteristics in consecutive frames, an inter-frame false alarm suppression method based on geometrical invariability is developed to improve the precision rate further. Quantitative analyses demonstrate the detecting precision of this proposed approach can be up to 97% and Receiver Operating Characteristic (ROC) curves further verify our method outperforms other state-of-the-arts methods in both detection rate and false alarm rate.

Details

Language :
English
ISSN :
20763417
Volume :
7
Issue :
6
Database :
Directory of Open Access Journals
Journal :
Applied Sciences
Publication Type :
Academic Journal
Accession number :
edsdoj.3babe4f0f8684a09afbb98e39aaa6790
Document Type :
article
Full Text :
https://doi.org/10.3390/app7060569