2016/01/29 by Mia Hubert, Hubert, Mia, Jakob Raymaekers +5 · 1 citation
Chemistry · Engineering · Mathematics · #Advanced Statistical Methods and Models #FOS: Computer and information sciences #Industrial Vision Systems and Defect Detection #Methodology (stat.ME) #Spectroscopy and Chemometric Analyses #stat.ME
paper · pdf · doi:10.48550/arxiv.1601.08133
arxiv created 2016/01/29 · openalex publication_date 2016/01/29 · arxiv updated 2016/02/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Surface, image and video data can be considered as functional data with a bivariate domain. To detect outlying surfaces or images, a new method is proposed based on the mean and the variability of the degree of outlyingness at each grid point. A rule is constructed to flag the outliers in the resulting functional outlier map. Heatmaps of their outlyingness indicate the regions which are most deviating from the regular surfaces. The method is applied to fluorescence excitation-emission spectra after fitting a PARAFAC model, to MRI image data which are augmented with their gradients, and to video surveillance data.