Organic electronics (electronic devices made from polymers or similar organic compounds) are an important class of thin film devices that exhibit flexibility, stretchability, softness and compatibility with biological systems, thus making them exceedingly attractive for bioelectronics and healthcare applications. Performance of these devices is highly correlated with the microstructure within the thin film. In other words, quantitative characterization of the microstructure is critical for understanding device performance. While several microscopy based imaging techniques – including Transmission Electron Microscopy (TEM) – are currently available to visualize the microstructure, analyzing the resulting data has remained predominantly manual. This makes extracting microstructural information from microscopic images subjective, and slow. We introduce a mathematical framework and associated software, GRATE, that integrates concepts from graph theory, image analysis and hierarchical (quad-tree) image decomposition to automatically extract a suite of microstructural features from TEM image data. Both local traits like lattice spacing, orientation and size measures as well as global traits like number and size distribution of crystallites are efficiently extracted. The software is modular, extensible and is packaged into a simple graphical user interface that can reduce time of adoption by practitioners.