This paper is a contribution to a benchmark concept definition and it proposes a set of image segmentation algorithms which should be included in any benchmark for vision system. The proposed alagorithms allow us to predict, estimate, and quantify many image/vision system parameters such as data acquisition rate, local and global system communications, machine capability to support recursive processings, data reorganization, different programming/ implementation models, system scalability, etc. The proposed three algorithms calculate: multithreshold image connect component labeling, image region identification (through two complementary steps: isotropic seed region growing and pixel fusion), and data reorganization. Formalized algorithms, which can be implemented on different plate-forms (sequential, parallel, distributed) supporting different programming and implementation paradigms (models) are given. Machine performance analysis and quantification via matching coefficients are proposed as well.