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Object Detection of NAO Robot Based on a Spectrum Model

  • Laixin Xie
  • Chunhua Deng
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10956)

Abstract

NAO robots often need to detect objects to accomplish its task. At present, color segmentation is popular with NAO robot vision tasks because of its lower-end specification. A spectrum segmentation algorithm is proposed to realize real time detection in this paper. Spectral model is the foundation of human visual system, which can separate objects of distinctive color characteristics from complex illumination. Compared with current methods, color threshold in our method is trained by objective color and background color, which can automatically separate foreground and background. In addition, this paper employs Support Vector Machine (SVM) to recognize segmented regions to increase detection accuracy. Experimental results demonstrate effectiveness of the proposed method.

Keywords

NAO robot Spectrum model Color segmentation Object detection 

Notes

Acknowledgment

This work was supported by the Hubei Province Training Programs of Innovation and Entrepreneurship for Undergraduates, 201710488036; Scientific and technological innovation fund for College Students of Wuhan University of Science and Technology, 17ZRC131; Scientific and technological innovation fund for College Students of Wuhan University of Science and Technology, 17ZRA116; Scientific and technological innovation fund for College Students of Wuhan University of Science and Technology, 17ZRA121.

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.College of Computer Science and TechnologyWuhan University of Science and TechnologyWuhanChina
  2. 2.Hubei Province Key Laboratory of Intelligent Information Processing and Real-Time Industrial SystemWuhanChina

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