ARFBF MORPHOLOGICAL ANALYSIS - APPLICATION TO THE DISCRIMINATION OF CATALYST ACTIVE PHASES

• Main Authors: Zhangyun Tan, Maxime Moreaud, Olivier Alata, Abdourrahmane M. Atto
• Format: Article
• Language: English
• Published: Slovenian Society for Stereology and Quantitative Image Analysis 2018-04-01
• Series: Image Analysis and Stereology
• Subjects: auto-regressive field; fractional Brownian field; HRTEM imaging; mathematical morphology; texture analysis
• Online Access: https://www.ias-iss.org/ojs/IAS/article/view/1624

This paper addresses the characterization of spatial arrangements of fringes in catalysts imaged by High Resolution Transmission Electron Microscopy (HRTEM). It presents a statistical model-based approach for analyzing these fringes. The proposed approach involves Fractional Brownian Field (FBF) and 2-D AutoRegressive (AR) modeling, as well as morphological analysis. The originality of the approach consists in identifying the image background as an FBF, subtracting this background, modeling the residual by 2-D AR so as to capture fringe information and, finally, discriminating catalysts from fringe characterizations obtained by morphological analysis. The overall analysis is called ARFBF (Auto-Regressive Fractional Brownian Field) based morphology characterization.