Robust scale invariant small target detection using the Laplacian scale-space theory

Sungho Kim; Yukyung Yang; Joohyoung Lee; Yongchan Park

doi:10.1117/12.777036

16 April 2008 Robust scale invariant small target detection using the Laplacian scale-space theory

Sungho Kim, Yukyung Yang, Joohyoung Lee, Yongchan Park

Proceedings Volume 6969, Signal and Data Processing of Small Targets 2008; 69691I (2008) https://doi.org/10.1117/12.777036
Event: SPIE Defense and Security Symposium, 2008, Orlando, Florida, United States

Abstract

This paper presents a new small target detection method using scale invariant feature. Detecting small targets whose sizes are varying is very important to automatic target detection in infrared search and track (IRST). The conventional spatial filtering methods with fixed sized kernel show limited target detection performance for incoming targets. The scale invariant target detection can be defined as searching for maxima in the 3D (x, y, and scale) representation of an image with the Laplacian function. The scale invariant feature can detect different sizes of targets robustly. Experimental results with real FLIR images show higher detection rate and lower false alarm rate than conventional methods. Furthermore, the proposed method shows very low false alarms in scan-based IR images than conventional filters.

Citation Download Citation

Sungho Kim, Yukyung Yang, Joohyoung Lee, and Yongchan Park "Robust scale invariant small target detection using the Laplacian scale-space theory", Proc. SPIE 6969, Signal and Data Processing of Small Targets 2008, 69691I (16 April 2008); https://doi.org/10.1117/12.777036

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