Robust Template Identification of Scanned Documents

Identification of low-quality scanned documents is not trivial in real-world settings. Existing research mainly focusing on similarity-based approaches rely on perfect string data from a document. Also, studies using image processing techniques for document identification rely on clean data and large differences among templates. Both these approaches fail to maintain accuracy in the context of noisy data or when document templates are too similar to each other. In this paper, a probabilistic approach is proposed to identify the document template of scanned documents. The proposed algorithm works on imperfect OCR output and document collections containing very similar templates. Through experiment and analysis, this novel probabilistic approach is shown to achieve high accuracy on different data sets.