Cognitive Information Processing

Contains reports on one research project.National Science Foundation (Grant GK-3373X1)Joint Services Electronics Program (Contract DAAB07-71-C-0300)National Institutes of Health (Grant 5 P01 GM14940-07

NBS monograph

From Introduction: "This report is the first of a series intended to provide a selective overview of research and development efforts and requirements in the somewhat overlapping fields of the computer and information sciences and technologies. The projected series of reports will attempt to outline the probable range of R & D activities in the computer and information sciences and technologies through selective reviews of the literature and to develop a reasonable consensus with respect to the opinions of workers in these and potentially related fields as to areas of continuing R & D concern for research program planning or review in these areas.

Aspects of n-tuple character recognition for a blind reading aid

This thesis was submitted for the degree of Doctor of Philosophy and was awarded by Brunel University.This thesis reports research conducted into a character recognition system suitable for use in a reading aid for the blind. A brief review of blind reading aids is given, showing the need for a device which is cheap, simple and effective. The structure of a proposed reading aid fulfilling these needs is outlined, with a list of the desired characteristics of each of its subsystems. The remainder of the thesis is concerned with research into just two of these subsystems: the input device and the character recognizer. A detailed review of pattern recognition by the n-tuple method is presented, followed by a description of the experimental techniques used in obtaining real data from a camera system, and in simulating various recognizer structures. The camera system and computer programs developed specifically for the research are described in detail. Several series of experiments are reported, concerned mainly with investigating problems associated directly with the blind reading aid, namely accommodation of multifont printed text and of the tracking errors inherent in data from a hand-held probe. A further series of experiments, aimed at improving the performance of the recognizer within fixed size constraints, i. e., optimisation, has a wider field of application. Finally suggestions are made as to how the recognizer might be implemented in a reading aid, using RAMs, ROMs, or PLAs as the main storage elements.Science Research Counci

Artificial Intelligence for Automated Design of Elevator Systems

Configuration and design of complex products represents a challenge in many application fields. The designer must take into account many different aspects and make decisions typically driven by experience while taking into account performance constraints and costs. Methods and tools for design automation represents a viable solution to such complex decision problems, giving also the possibility to optimize the performance of the final product on particular context-driven aspects. Artificial intelligence (AI) algorithms can help in dealing with complexity and enhance the current tools by supplying solutions in feasible time. My research is concerned with the development and testing of different artificial intelligence (AI) techniques to automate the design of elevators. Elevator design is a problem with many interesting aspects like the need to deal with a hybrid search state space (continuous and discrete variables) constrained by design requirements and safety regulations. The study, design and integration of AI techniques in this particular application field can provide the end user with design automation tools that output feasible solutions within acceptable computation times. My research considered AI techniques such as special-purpose heuristic search, genetic algorithms and constraint satisfaction to solve elevator configuration problems. I tested them considering different setups and parts of the whole design process. I have also implemented a tool L IFT C REATE , available as a web application. L IFT C REATE leverages the findings of my research to automate the design of elevators and, to the best of my knowledge, there is currently no similar tool publicly available from either academia or industry that provides the same level of design automation

Document preprocessing and fuzzy unsupervised character classification

This dissertation presents document preprocessing and fuzzy unsupervised character classification for automatically reading daily-received office documents that have complex layout structures, such as multiple columns and mixed-mode contents of texts, graphics and half-tone pictures. First, the block segmentation algorithm is performed based on a simple two-step run-length smoothing to decompose a document into single-mode blocks. Next, the block classification is performed based on the clustering rules to classify each block into one of the types such as text, horizontal or vertical lines, graphics, and pictures. The mean white-to-black transition is shown as an invariance for textual blocks, and is useful for block discrimination. A fuzzy model for unsupervised character classification is designed to improve the robustness, correctness, and speed of the character recognition system. The classification procedures are divided into two stages. The first stage separates the characters into seven typographical categories based on word structures of a text line. The second stage uses pattern matching to classify the characters in each category into a set of fuzzy prototypes based on a nonlinear weighted similarity function. A fuzzy model of unsupervised character classification, which is more natural in the representation of prototypes for character matching, is defined and the weighted fuzzy similarity measure is explored. The characteristics of the fuzzy model are discussed and used in speeding up the classification process. After classification, the character recognition procedure is simply applied on the limited versions of the fuzzy prototypes. To avoid information loss and extra distortion, an topography-based approach is proposed to apply directly on the fuzzy prototypes to extract the skeletons. First, a convolution by a bell-shaped function is performed to obtain a smooth surface. Second, the ridge points are extracted by rule-based topographic analysis of the structure. Third, a membership function is assigned to ridge points with values indicating the degrees of membership with respect to the skeleton of an object. Finally, the significant ridge points are linked to form strokes of skeleton, and the clues of eigenvalue variation are used to deal with degradation and preserve connectivity. Experimental results show that our algorithm can reduce the deformation of junction points and correctly extract the whole skeleton although a character is broken into pieces. For some characters merged together, the breaking candidates can be easily located by searching for the saddle points. A pruning algorithm is then applied on each breaking position. At last, a multiple context confirmation can be applied to increase the reliability of breaking hypotheses

The effectiveness of features in pattern recognition

Imperial Users onl