A system for inspecting metal parts in a production line at a rate of 300 parts per minute is described. During inspection, the parts are classified according to a wide range of predefined defect types, consisting of both structural defects (dents, bulges, scratches, splits), and textural defects (acid stains, paint, anneal, etc.). Each flaw has its own rejection criterion, which is not directly correlated to its size, shape or contrast. The image is modeled by utilizing a-priori information concerning the nature of the defects and the specific illumination configuration. We apply low level feature detection in several resolutions in order to derive the specific signature of defect. Classification is then done on the reduced feature space for flaw identification and severity decision. The algorithms are implemented with dedicated image processing hardware, working in a pipeline fashion on a dedicated synchronized video bus to achieve the high speed requirements of the system.