Abstract

As the most pervasive method of individual identification and document authentication, signatures present convincing evidence and provide an important form of indexing for effective document im- age processing and retrieval in a broad range of applications. In this work, we developed a fully automatic signature-based document image retrieval system that handles: 1) Automatic detection and segmentation of signatures from document images and 2) Translation, scale, and ro- tation invariant signature matching for document image retrieval. We treat signature retrieval in the unconstrained setting of non-rigid shape matching and retrieval, and quantitatively study shape representations, shape matching algorithms, measures of dissimilarity, and the use of multiple query instances in document image retrieval. Extensive experi- ments using large real world collections of English and Arabic machine printed and handwritten documents demonstrate the excellent perfor- mance of our system. To the best of our knowledge, this is the first auto- matic retrieval system for general document images by using signatures as queries, without manual annotation of the image collection.