Dicot leaves are comprised of a heterogeneous mosaic of jig-saw-puzzle piece shaped pavement cells that vary greatly in size and the complexity of their shape. Given the importance of the epidermis and this particular cell type for leaf expansion, there is a strong need to understand how pavement cells morph from a simple polyhedral shape into highly lobed and interdigitated cells. At present, it is still unclear how and when the patterns of lobing are initiated in pavement cells, and one major technological bottleneck to address the problem is the lack of a robust and objective methodology to identify and track lobing events during the transition from simple cell geometry to lobed cells. We developed a convex-hull based algorithm termed LobeFinder to identify lobes, quantify geometric properties, and create a useful graphical output for further analysis. The algorithm was validated against manually curated cell images of pavement cells of widely varying sizes and shapes. The ability to objectively count and detect new lobe initiation events provides an improved quantitative framework to analyze mutant phenotypes, detect symmetry-breaking events in time-lapse image data, and quantify the time-dependent correlation between cell shape change and intracellular factors that may play a role in the morphogenesis process.