OCR tools, extensively used for administrative purposes for adress, forms, checks reading, properly works with rather clean, flat and paper documents. RECITE aims at extending OCR application fors machine vision for objects with different surfaces (metal and so on) and with very various characters. Close to natural scene text understanding, this project focuses on interactively configurable recognition software in order to give access to non-experts people (in SMEs for instance). Hence, the main goal is to enable the creation of dedicated recognizers for particular applications. Very general OCR may be applied but we are convinced that performance will be lower.
Based on smart dialogues between the computer and the end-user, particularities of the application, degradations embedded into images will be semi-automatically defined in order to build an efficient recognizer.
Additionally, some challenges are met such as extraction and recognition of engraved/embossed characters, which are limitations of systems dealing with natural scene text. In that context, one example is first taken in order to make further the model more versatile: the recognition of engraved characters into metallic and reflective surfaces in uncontrolled environment.
Keywords: Text recognition, Natural Scene, Auto-configurable Systems