Acta Photonica Sinica ›› 2019, Vol. 48 ›› Issue (6): 610002-0610002.doi: 10.3788/gzxb20194806.0610002

• Image Processing • Previous Articles     Next Articles

Method of Aircraft Target Detection in Remote Sensing Images Based on Rotation-invariant Feature

LIN Yi, ZHAO Ming, PAN Sheng-da, AN Bo-wen   

  1. College of Information Engineering, Shanghai Maritime University, Shanghai 201306, China
  • Received:2019-01-07 Online:2019-06-25 Published:2019-04-22
  • Supported by:

    The National Natural Science Foundation of China (Nos. 61302132, 61504078, 41701523), "Chenguang" Program of Shanghai Municipal Education Commission and Shanghai Education Development Foundation (No.13CG51), Foundation of Guangxi Educational Committee (No.YB2014207)


To improve the accuracy of the multi-target detection for remote sensing image in the dynamic aircraft supervision system, a target detection method was proposed. First, two new rotation-invariance features, named center-particle angle and H-vector, are introduced. Then, the sliding detection window is used to calculate the center-particle angle and correlation coefficient of H-vector. Also, the corresponding scoring system is designed according to the matching degree of template feature to determine if there is a plane in the detection window under the assistant of non-maximum suppression. The remote sensing images of aircraft under different scenes were detected in experiment, the results show that the average F1-score reaches above 90%, and both of the recall rate and precision are higher than some traditional methods in wider scope of application.

Key words: Target detection, Feature matching, Aircraft supervision, Pattern recognition, Remote sensing images

CLC Number: