The evaluation of image and video segmentation results assumes a critical role for the selection of appropriate segmentation algorithms, as well as the adjustment of their parameters for optimal segmentation performance in the context of a given application. The current practice for the evaluation of video segmentation quality is based on subjective testing, which is an expensive and time-consuming process. Objective segmentation quality evaluation techniques can alternatively be used, once appropriate algorithms become available. Currently this is a field under development and this contribution proposes evaluation methodologies and objective segmentation quality metrics both for individual objects and for complete segmentation partitions. Standalone and relative evaluation metrics are proposed, to be used when a reference segmentation is missing, or available for comparison, respectively.