This paper describes a feature calibration scheme for use in embedding and detecting watermarks in document images. Such watermarks have a variety of uses, including copyright protection, content identification, and tamperproofing. In general, a watermark is encoded as a displacement of certain features that can be extracted from target document images. One of the technical challenges is reliable detection of the displacement when images are distorted by print-and-scan processes.We propose a calibration method that uses the difference between two features extracted from two sets of partitions arranged symmetrically. Since this method counterbalances the cumulative effects on the features of distortions added in the print-and-scan process, the displacement can be reliably detected. The feasibility of the method was investigated by using the average width of character strokes is used as a feature.
This paper proposes a new algorithm for detecting character strings in an image containing illustrations and characters. It also describes a part number entry system that utilizes this algorithm. The algorithm detects character strings by investigating the horizontal boundaries of rectangles representing character strings. It can be performed at high speed, and can detect characters touching an illustration. Using this algorithm, the part number entry system extracts areas of part numbers scattered among illustrations and then recognizes them. This is a software program implemented on a personal computer, and is composed of four sub-programs: detection of character strings, character recognition, post-processing, and flexible user-interface for error correction.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.