We address the problem of providing input to a novel method of interpreting photoelastic data for performing experimental stress analysis of models of engineering components. This method employs conventional photoelastic data relating to the directions of the principal stresses in the specimen (isoclinic data), along with the difference in principal stresses (isochromatic data). Both are used within an inverse boundary element model to reconstruct the load conditions at the model boundary and hence to recover the principal stresses in the specimen without recourse to numerical integration of shear stress gradient. We describe methods of obtaining unwrapped isoclinic and isochromatic phase maps from sequences of images captured within a computer-controlled polariscope. A boundary element model of the specimen, congruent with the isoclinic and isochromatic phase maps, is obtained from an image captured within the polariscope under either traditional lighting conditions or by configuring the polariscope to provide a light field background. Image segmentation reveals the boundary of the specimen, which is then described in terms of simple geometric primitives. Boundary points and geometric descriptions are both used to produce the final boundary element model. The techniques described have been applied to a number of contact specimens; results are presented and discussed.
Stroke is a major cause of disability and health care expenditure around the world. Existing stroke rehabilitation methods can be effective but are costly and need to be improved. Even modest improvements in the effectiveness of rehabilitation techniques could produce large benefits in terms of quality of life. The work reported here is part of an ongoing effort to integrate virtual reality and machine vision technologies to produce innovative stroke rehabilitation methods. We describe a combined object recognition and event detection system that provides real time feedback to stroke patients performing everyday kitchen tasks necessary for independent living, e.g. making a cup of coffee. The image plane position of each object, including the patient’s hand, is monitored using histogram-based recognition methods. The relative positions of hand and objects are then reported to a task monitor that compares the patient’s actions against a model of the target task. A prototype system has been constructed and is currently undergoing technical and clinical evaluation.
The English city of Nottingham is widely known for its rich history and compelling folklore. A key attraction is the extensive system of caves to be found beneath Nottingham Castle. Regular guided tours are made of the Nottingham caves, during which castle staff tell stories and explain historical events to small groups of visitors while pointing out relevant cave locations and features. The work reported here is part of a project aimed at enhancing the experience of cave visitors, and providing flexible storytelling tools to their guides, by developing machine vision systems capable of identifying specific actions of guides and/or visitors and triggering audio and/or video presentations as a result. Attention is currently focused on triggering audio material by directing the beam of a standard domestic flashlight towards features of interest on the cave wall. Cameras attached to the walls or roof provide image sequences within which torch light and cave features are detected and their relative positions estimated. When a target feature is illuminated the corresponding audio response is generated. We describe the architecture of the system, its implementation within the caves and the results of initial evaluations carried out with castle guides and members of the public.
Using information theory, this investigation propose a novel technique for shape description which is invariant to translation, rotation and in most cases also to scale. This new numeric shape descriptor is based on the measure of rotational information content of an image. In this paper we first review some popular metric shape description features. These features are then used to analyze the feasibility of using the rotational information for shape description, and by means of a comparative study we show how the rotational information is related to well known metric shape descriptors such as area, circularity and elongation. Finally, the results obtained are discussed and analyzed, and conclusions drawn in terms of the suitability of the technique for shape description in image recognition problems.
One of the main problems faced in the development of pattern recognition algorithms is assessment of their performance. This paper describes the development of a novel technique for the assessment of information content of 2-D patterns encountered in practical pattern recognition problems. The technique is demonstrated by its application to multi-font typed character recognition. In this work we first developed an information model applicable to any pattern, and its elaboration to measure recognition performance, and second we used this model to derive parameters such as the resolution required to distinguish between the patterns. This has resulted in a powerful method for assessing the performance of any pattern recognition system.
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