This paper presents an identification technique that au- tomatically detects the underlying script and orientation of scanned document images. In the proposed technique, document script and orientation are identified by using the stroke density and distribution, which convert each docu- ment image into a document vector. For each script at each orientation, a number of reference document vectors are first constructed. Script and orientation of the query document are then determined according to the similar- ity between the query document vector and multiple pre- constructed reference document vectors by using the K- nearest neighbor algorithm. Experiments show that the pro- posed technique is tolerant to the document skew and able to detect orientations of documents of different scripts.