Material recognition based on a pulsed time-of-flight camera - Details

Author：

Zhang, Jizhong (Zhang, Jizhong.) | Lang, Shinan (Lang, Shinan.) | Wu, Qiang (Wu, Qiang.) | Liu, Chuan (Liu, Chuan.)

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Abstract：

This　study　presents　a　method　for　material　recognition　using　a　pulsed　time-of-flight　(ToF)　camera.　The　method　measures　the　material　bidirectional　reflectance　distribution　function　(BRDF)　as　a　feature　for　material　recognition　by　a　pulsed　ToF　camera.　We　use　the　measurements　of　incident　light　at　different　angles　to　form　the　BRDF　feature　vectors.　The　feature　vectors　are　used　to　build　a　training　and　test　set　to　train　and　validate　a　classifier　to　perform　the　recognition.　We　choose　the　radial　basis　function　(RBF)　neural　network　as　a　classifier　based　on　the　nonlinear　characteristics　of　material　BRDF.　Finally,　we　construct　a　turntable-based　measurement　system　and　use　the　material　BRDF　as　the　feature　for　classifying　a　variety　of　materials　including　metals　and　plastics.　The　optimized　RBF　neural　network　can　achieve　a　recognition　accuracy　of　94.6%.　©　2019　IEEE.

Keyword：

Reflection Radial basis function networks Cameras Distribution functions Classification (of information)

Author Community：

[ 1 ] [Zhang, Jizhong]Beijing University of Technology, Faculty of Information Technology, Beijing, China
[ 2 ] [Lang, Shinan]Beijing University of Technology, Faculty of Information Technology, Beijing, China
[ 3 ] [Wu, Qiang]Beijing University of Technology, Faculty of Information Technology, Beijing, China
[ 4 ] [Liu, Chuan]Beijing University of Technology, Faculty of Information Technology, Beijing, China