The general global 2-D shape recognition problem of objects in digital scenes is discussed. A new technique -- Normalized Interval Vertex Descriptors (NI/VD) -- for representing contours is introduced to the field of object recognition. This technique, which is derived from the physical characteristic of the silhouette of the object (corners and sides), is proven to be effective in recognizing objects that can be more or less represented or approximated by polygons. Typical examples of these classes are man-made objects like planes, missiles, mechanical parts, etc. Normalized Interval Vertex Descriptors provide an accurate representation for objects which is robust to three main sources of classification errors, namely: scale change, translation and rotation. Because of this robustness and other advantages of this implementation, its use proves to be very effective for recognizing objects in arbitrary positions within the field of view (FOV) and for objects at varying distances from the sensor or for various sensor zoom factors. Compactness of the representation, on the other hand, allows the implementation of faster object recognition systems.