Abstract
TImage matching and recognition of architectural decoration elements is the basis of architectural decoration design. The traditional matching and recognition methods have low precision and high complexity, so they are not suitable for the image matching and recognition of architectural decoration elements under complex conditions. Based on the analysis of the basic particle swarm optimization algorithm, the nonlinear asynchronous strategy is adjusted to change the fixed constant mode of the learning factor to balance the local and global search ability of the algorithm in the iterative process. At the same time, the vitality factor was introduced to mutate the inactivated particles to improve the population diversity. The experimental results show that compared with the traditional algorithm, this method improves the image matching and recognition accuracy of architectural decoration elements.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
