The Camouflage Color Target Detection with Deep Networks

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10636)

Abstract

The camouflage color target is similar to the background, so the detection is very difficult. How to identify the camouflage color target is still a challenging visual task. In order to solve the problem, we propose a camouflage color target detection algorithm based on image enhancement. Firstly, the image enhancement algorithm is used to realize the difference between the target and the background feature. Secondly, the region proposal network (RPN) is used to realize the accurate positioning of the specific target, and the extraction area ROI is identified by the classification layer in the deep neural network. Finally, we realize the detection with a camouflage color target. In this paper, the detection algorithm received better detection results in the leaves of butterfly and chameleon data collection.

Keywords

Target detection Camouflage color CLAHE Faster R-CNN 

Notes

Acknowledgments

The paper was supported in part by the National Natural Science Foundation (NSFC) of China under Grant No. 61365003 and Gansu Province Basic Research Innovation Group Project No. 1506RJIA031.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.College of Electrical and Information EngineeringLanzhou University of TechnologyLanzhouChina

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