The analysis of imaging data derived from micro-Fourier transform infrared (μFTIR) microscopy is a powerful tool allowing the analysis of microplastics enriched on membrane filters. In this study we present an automated approach to reduce the time demand currently needed for data analyses. We developed a novel analysis pipeline, based on the OPUS© Software by Bruker, followed by image analysis with Python and Simple ITK image processing modules. By using this newly developed pipeline it was possible to analyse datasets from focal plane array (FPA) μFTIR mapping of samples containing up to 1.8 million single spectra. All spectra were compared against a database of different synthetic and natural polymers by various routines followed by benchmark tests with focus on accuracy and quality. The spectral correlation was optimized for high quality data generation, which allowed image analysis. Based on these results an image analysis approach was developed, providing information on particle numbers and sizes for each polymer detected. It was possible to collect all data with relative ease even for complex sample matrices. This approach significantly decreases the time demand for the interpretation of complex FTIR-imaging data and significantly increases the data quality.