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The text develops a global shape model and applies it to the analysis of real pictures acquired with a visible light camera under varying conditions of optical degradation. Computational feasibility of the algorithms derived from this model is achieved by analytical means. The aim is to develop methods for image understanding based on structured restoration, for example automatic detection of abnormalities. The limits of applicability of the algorithms are also traced by making the optical degradations more and more severe until the algorithms no longer succeed in their task. This book is suitable for an advanced undergraduate or graduate seminar in pattern theory, or as an accompanying book for applied probability, computer vision or pattern recognition.
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The text develops a global shape model and applies it to the analysis of real pictures acquired with a visible light camera under varying conditions of optical degradation. Computational feasibility of the algorithms derived from this model is achieved by analytical means. The aim is to develop methods for image understanding based on structured restoration, for example automatic detection of abnormalities. The limits of applicability of the algorithms are also traced by making the optical degradations more and more severe until the algorithms no longer succeed in their task. This book is suitable for an advanced undergraduate or graduate seminar in pattern theory, or as an accompanying book for applied probability, computer vision or pattern recognition.
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