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Multiresolutional Fault-Tolerant Sensor Integration and Object Recognition in Images.

Abstract

This dissertation applies multiresolution methods to two important problems in signal analysis. The problem of fault-tolerant sensor integration in distributed sensor networks is addressed, and an efficient multiresolutional algorithm for estimating the sensors\u27 effective output is proposed. The problem of object/shape recognition in images is addressed in a multiresolutional setting using pyramidal decomposition of images with respect to an orthonormal wavelet basis. A new approach to efficient template matching to detect objects using computational geometric methods is put forward. An efficient paradigm for object recognition is described

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Louisiana State University

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Last time updated on 26/10/2023

This paper was published in Louisiana State University.

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