This paper is concerned with the problem of model based recognition of polyhedral objects from a single perspective view. A hypothesise-verify paradigm based on the use of high level knowledge constraints derived from local shape properties is presented. In the recognition system, two high level features, namely triangle pair and quadrilateral are employed as key features for model invocation and hypothesis generation. A verification process for performing a detailed check on the model to scene correspondences is developed. To reduce the number of implausible hypotheses generated from scene to model intermediate feature assignments, two geometrical contraints, namely distance and angle constraints are employed. A list of closed polygons and C-triple pairs extracted from a 2D intensity image by means of edge and intermediate feature detection process is used as an input to the matching system. The intermediate feature grouping process starts by identifying junctions created by pairs of line segments and then forms triples by combining pairs of junctions which share a common line. These triples are then scanned by procedure which connects them into meaningful geometric structures. As a byproduct of the recognition method, the relative pose of the 3D polyhedral objects with respect to the camera is recovered. Extensive experimental results are reported to confirm the feasibility of the proposed method.