Fluoropolymer is of a unique interest due to its excellent oil and water repellent properties, satisfactory thermal stability, lower surface energy and high refractive index. They are used in various ways, especially as binders in batteries, since they have the ability to hold active materials. However, these unique properties of polymers are affected by the aging which then greatly affects the polymers’ properties. Therefore, we are quantifying the changes by crystallization kinetics. Two methods were explored to classify and segment features. First, manual labels on crystallites were generated using Gwyddion. Gwyddion is a commonly used scanning probe microscopy (SPM) for AFM image processing. This method establishes our ground truth. The second method applies a semi-automated algorithm for image segmentation. Areas of the crystallites were calculated and then used as a metric to compare the two methods. Our main goal is to shift from open source software to automated image segmentation methods. Therefore, we are trying to incorporate our insights using Gwyddion into our automated workflow for high throughput image analysis.