Summary With the realization that bacteria display phenotypic variability among cells and exhibit complex subcellular organization critical for cellular function and behavior, microscopy has re‐emerged as a primary tool in bacterial research during the last decade. However, the bottleneck in today's single‐cell studies is quantitative image analysis of cells and fluorescent signals. Here, we address current limitations through the development of Oufti, a stand‐alone, open‐source software package for automated measurements of microbial cells and fluorescence signals from microscopy images. Oufti provides computational solutions for tracking touching cells in confluent samples, handles various cell morphologies, offers algorithms for quantitative analysis of both diffraction and non‐diffraction‐limited fluorescence signals and is scalable for high‐throughput analysis of massive datasets, all with subpixel precision. All functionalities are integrated in a single package. The graphical user interface, which includes interactive modules for segmentation, image analysis and post‐processing analysis, makes the software broadly accessible to users irrespective of their computational skills. Oufti is an interactive, open source software package built for high throughput quantification of microscopy images. Oufti performs cell detection, localization of diffraction‐limited spots as well as boundary determination of image objects beyond the diffraction limit. Due to parallel processing, it is able to perform these tasks on large (>1Gb) datasets, which can be further expanded by high performance computing centers. Oufti also provides post‐processing tools for the statistical characterization of data following image analysis.