Automatic targets recognition(ATR) of artificial objects in high resolution remote sensing images can be divided into two categories by the properties of targets. The first such building, a harbor which has fixed location and stable out looking. The other one, for example aircraft, whose location and posture is sensitive to the moment. Due to the variable sizes, colors, orientations, and complex background, aircraft detection is a difficult task in high resolution remote sensing images. In this paper, a simple and effective aircraft detection method with a single template is proposed, which exactly locates the object by outputting its geometric center, location and orientation. Compare to traditional method,this method only needs critical feature in the local areas of target and a binary template of aircraft. Compare to traditional Feature + Classifier method, it’s easy, simple and don’t need outline training,but also get high precision and low false rate in the same complicate background.
[1]
陳建銘,et al.
衛星影像中飛機機型之辨識; Aircraft Type Recognition in Satellite Images
,
2003
.
[2]
Christopher G. Harris,et al.
A Combined Corner and Edge Detector
,
1988,
Alvey Vision Conference.
[3]
S. M. Steve.
SUSAN - a new approach to low level image processing
,
1997
.
[4]
Gang Liu,et al.
Co-segmentation of aircrafts from high-resolution satellite images
,
2012,
2012 IEEE 11th International Conference on Signal Processing.
[5]
Hans P. Moravec.
Towards Automatic Visual Obstacle Avoidance
,
1977,
IJCAI.
[6]
Tsorng-Lin Chia,et al.
Using cross-ratios to model curve data for aircraft recognition
,
2003,
Pattern Recognit. Lett..
[7]
Shiming Xiang,et al.
Aircraft Detection by Deep Belief Nets
,
2013,
2013 2nd IAPR Asian Conference on Pattern Recognition.