Local Concave-and-Convex Micro-Structure Patterns for texture classification
作者：
Highlights：
• A formal definition of Concave and Convex Binary Thresholding Functions are introduced.
• Two new LBP-like descriptors: Local Concave and Convex Micro-Structures Pattern (LCvMSP and LCxMSP) descriptors are proposed.
• LCvMSP and LCxMSP are concatened into a single vector feature to obtain the multiscale LCCMSP descriptor.
• A statistical hypothesis testing based method for parameters optimization on several datasets is proposed.
• The proposed methods demonstrate superior performance to 79 LBP variants and non-LBP methods over 13 texture datasets.
摘要
•A formal definition of Concave and Convex Binary Thresholding Functions are introduced.•Two new LBP-like descriptors: Local Concave and Convex Micro-Structures Pattern (LCvMSP and LCxMSP) descriptors are proposed.•LCvMSP and LCxMSP are concatened into a single vector feature to obtain the multiscale LCCMSP descriptor.•A statistical hypothesis testing based method for parameters optimization on several datasets is proposed.•The proposed methods demonstrate superior performance to 79 LBP variants and non-LBP methods over 13 texture datasets.
论文关键词：LBP,Local concave-and-convex characteristics,LCvMSP,LCxMSP,LCCMSP,Feature extraction,Texture classification
论文评审过程：Received 8 April 2017, Revised 11 September 2017, Accepted 5 November 2017, Available online 7 November 2017, Version of Record 17 November 2017.
论文官网地址：https://doi.org/10.1016/j.patcog.2017.11.005
