Spotting Words in Latin, Devanagari and Arabic Scripts

A system for spotting words in scanned document images in three scripts, Devanagari, Arabic and Latin is described. Three main components of the system are a word segmenter, a shape based matcher for words and a search interface. The user gives a query which can be either a word image or text. The candidate words that are searched in the documents are retrieved and ranked, where the ranking criterion is a similarity score between the query and the candidate words based on global word shape features. This renders the word spotting technique to be independent of the script used. The performance of system is seen to be better for printed text as compared to handwritten. For handwritten English, a precision of 60% was obtained at a recall of 50%. An alternate approach comprising of prototype selection and word matching, that yields a better performance for handwritten documents is also discussed. For printed Sanskrit documents, a precision as high as 90% was obtained at a Recall of 50%.