Evaluation of an algorithm for finding a match for a random texture pattern in a large image database is presented. The algorithm was designed assuming that the random pattern may be subject to misregistration relative to its representation in the database and assuming that it may have missing parts. The potential applications involve authentication of legal documents, bank notes, or credit cards, where thin fibers are embedded randomly into the document medium during medium fabrication. The algorithm achieves image matching by a three-step hierarchical procedure, which starts by matching parts of fiber patterns while solving the misregistration problem and ends up by matching complete fiber patterns. Performance of the algorithm is studied both theoretically and experimentally. Theoretical analysis includes the study of the probability that two documents have the same pattern, and the probability of the algorithm establishing a wrong match, as well as the algorithm's performance in terms of processing time. Experiments involving over 250,000 trials using databases of synthetic documents, containing up to 100,000 documents, were used to confirm theoretical predictions. In addition, experiments involving a database containing real images were conducted in order to confirm that the algorithm has potential in real applications.

This paper describes designing and testing systems for inspection of web materials using a development environment simulated in software. This environment comprises five sub-systems: sensing, detection, characterization, validation and decision making. Given a specific inspection problem the system is customized by incorporating specific algorithms into each of the sub-systems. In order to illustrate the customization, the paper uses an example of inspection of a nonwoven material. The inspection objective is to quantify the randomness and homogeneity across the material. This task requires using statistical modeling to characterize texture. The paper discusses a theoretical approach based on a Poissonian model, its efficient implementation, and steps required to implement this procedure online.

This paper describes part of a study aimed at developing a computer-based aid for mammogram screening that makes a detailed comparison between mammograms of the same patient acquired at different screenings and detects changes indicative of cancer. The focus is on determining control points in two mammograms; these points are used to put two mammograms into correspondence. The paper details the algorithm for identifying the potential control points and establishing the correspondence between the two sets of control points. The algorithm's performance was evaluated by three observers, one of whom is an experienced radiologist, and found to be adequate.

The authors propose a new methodology for identification of feature points in non-structured texture images and suggest how they can be used to perform regional registration when precise (pixel-wise) registration is not possible. The specific motivation behind this work is the analysis of sequences of mammographic images of the same patient with the objective of detecting changes indicative of cancer. Because of intractability of precise mammogram registration the authors propose regional mammogram registration and comparison by using feature points. This paper focuses on extraction and pairing of the feature points. The proposed technique is tested on 50 mammogram pairs and verified by visual inspection involving three human subjects, an experienced radiologist and two casual observers.

This paper describes the development environment for the design and testing of an expert system for web material inspection. The environment incorporates five sub-systems: sensing, detection, characterization, feature analysis, and classification. Each sub-system consists of a number of modules targeted at performing specific functions and containing adaptive image processing and pattern recognition algorithms. An example of defect classification in web materials is considered. The results are summarized and interpreted.

An approach to authenticating/recognizing documents based on random patterns embedded into the document medium is described. The random patterns are formed by embedding short fibers during medium fabrication and the resulting documents have extremely high uniqueness. Therefore, these patterns offer an effective anti-counterfeiting measure. The proposed algorithm compares a document under consideration to all documents contained in a database assuming that the newly acquired document may be rotated and translated relative to its match in the database, and/or parts of the document may be missing. The algorithm has been tested on over 2000 synthetic images always giving satisfactory results.>