We report an algorithm to identify the script of each word in a document image. We start with a bi-script scenario which is later extended to tri-script and then to eleven-script scenario. A database of 20 000 word of different font styles and sizes has been collected and used for each script. Effectiveness of Gabor and DCT features have been independently evaluated using nearest neighbour, linear discriminated and SVM Classifiers. The combination of Gabor features with nearest neighbour or SVM Classifier shows promising results: i.e., over 98% for bi-script and tri-script case and above 89% for the eleven-script scenario.