Signature-based document image retrieval

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 image 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 rotation 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 experiments using large real world collections of English and Arabic machine printed and handwritten documents demonstrate the excellent performance of our system. To the best of our knowledge, this is the first automatic retrieval system for general document images by using signatures as queries, without manual annotation of the image collection.