Many shape recognition techniques have been presented in literature, most of them from a quantitative perspective. Research has shown that qualitative reasoning better reflects the way humans deal with spatial reality. The current qualitative techniques are based on break points resulting in difficulties in comparing analogous relative positions along polylines. The presented shape representation technique is a qualitative approach based on division points, resulting in shape matrices forming a shape data model and thus forming the basis for a cognitively relevant similarity measure for shape representation and shape comparison, both locally and globally.