Premium
Research on infrared image segmentation and fusion of substation based on modified unit‐linking‐pulse coupled neural networks and affine speeded up robust feature
Author(s) -
Peng Daogang,
Wang Lanqing,
Chen Yuewei,
Xia Fei,
Qian Yuliang
Publication year - 2019
Publication title -
microwave and optical technology letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.304
H-Index - 76
eISSN - 1098-2760
pISSN - 0895-2477
DOI - 10.1002/mop.31842
Subject(s) - artificial intelligence , computer vision , affine transformation , segmentation , fault (geology) , feature (linguistics) , computer science , image fusion , fusion , artificial neural network , infrared , pattern recognition (psychology) , point (geometry) , image segmentation , matching (statistics) , image (mathematics) , mathematics , geology , optics , physics , linguistics , philosophy , seismology , pure mathematics , geometry , statistics
Abstract Aiming at the problem of fault point temperature reading and positioning, target device segmentation, and fault point matching fusion in infrared warning system of substation inspection robot, MUL‐PCNN and ASURF are applied to realizing accurate fusion between the fault area in infrared image and visual image. The experimental results show that this method has certain value in the aspect of infrared image segmentation and fusion of substation.