Measuring the effects of mutation, natural variation or treatment on the development of plant form is often complicated by the shapes, dynamics or small size of the organismal structures under study. This limits accuracy and throughput of measurement and thereby limits progress toward understanding the underlying gene networks and signaling systems. A computer-vision platform based on electronic image capture and shape-analysis algorithms was developed as an alternative to the mostly manual methods of measuring seedling development currently in use. The spatial and temporal resolution of the method is in the range of microns and minutes, respectively. The algorithm simultaneously quantifies apical hook opening and inhibition of hypocotyl elongation during photomorphogenesis of Arabidopsis thaliana seedlings. It can determine when and where gravitropic curvature develops along the root axis in A. thaliana and Medicago truncatula seedlings. Novel features of gravitropic curvature development were discovered as a result of the high resolution. The computer-vision algorithms developed and demonstrated here could be used to study mutant phenotypes in detail, to form the basis of a high-throughput screening platform, or to quantify natural variation in a population of plants.