Skip to Main Content
This paper deals with signature based document retrieval from documents with cluttered background. Here, a signature object is characterized by spatial features computed from recognition result of background blobs. The background blobs are computed by analyzing character holes and water reservoir zones in different directions. For the indexation purpose, a codebook of the background blobs is created using a set of training data. Zernike Moment feature is extracted from each blob and a K-Mean clustering algorithm is used to create the codebook of blobs. During retrieval, Generalized Hough Transform (GHT) is used to detect the query signature and a voting is casted to find possible location of the query signature in a document. The spatial features computed from background blobs found in the target document are used for GHT. The peak of votes in GHT accumulator validates the hypothesis of the query signature. The proposed method is tested on a collection of mixed documents (handwritten/printed) of various scripts and we have obtained encouraging results from the experiments.