We present a multiagent computer segmentation system, named KISS. This system has been implemented under our multiagent problem solver (MAPS), a generic programming environment dedicated to multiagent architecture design. MAPS entails a basic distinction between object-oriented and action-oriented agents, which allows flexible alternation between figurative and operative focusing tasks. KISS demonstrates the applicability of a multiagent approach to computer vision by offering a clear distribution of knowledge among several agents, dedicated successively to low-, intermediate-, and high-level analysis steps. Segmentation is approached through a cooperative analysis, involving both region and contour-based detection. Interpretation of patterns is made under three successive steps, using geometrical, relational, and semantic labeling, respectively. Such interpretation makes it possible to guide the selection of handling procedures to improve the initial segmentation. The potential power of such an approach is exemplified by its application to muscle fiber analysis.