Scale-space spatio-temporal random fields: Application to the detection of growing microbial patterns from surface roughness
作者：
Highlights：
• Spatio-temporal statistical modelling of surface roughness acquired at multiple time points.
• Scale-space analysis of multitemporal surface measurements.
• Statistical threshold based on scale-space spatio-temporal random field model.
• Detection of spatiotemporal patterns of unknown scales.
• Discrimination of spatiotemporal patterns based on the growth evolution.
摘要
Highlights•Spatio-temporal statistical modelling of surface roughness acquired at multiple time points.•Scale-space analysis of multitemporal surface measurements.•Statistical threshold based on scale-space spatio-temporal random field model.•Detection of spatiotemporal patterns of unknown scales.•Discrimination of spatiotemporal patterns based on the growth evolution.
论文关键词：Spatio-temporal modeling,Scale-space analysis,Gaussian random field,Detection,Surface roughness,Microbial patterns
论文评审过程：Received 1 October 2015, Revised 30 March 2016, Accepted 31 March 2016, Available online 30 April 2016, Version of Record 26 May 2016.
论文官网地址：https://doi.org/10.1016/j.patcog.2016.03.034
