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Proceedings Paper

Dynamic adjustment of regularization parameters for the fusion of edge features and noisy dense surfaces
Author(s): C. Richardson; Renato A. Salinas Silva; Mongi A. Abidi
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Paper Abstract

Data fusion provides tools for solving problems which are characterized by distributed and diverse information sources. Many robotic applications need to retrieve particular properties from a scene; so it is necessary to use multiple knowledge sources since a single sensory modality cannot capture all of the physical causes of a given edge feature. In this paper we focus on the problem of extracting features such as image discontinuities from both synthetic and real images. Since edge detection and surface reconstruction are ill-posed problems according to Hadamard, Tikhonov's regularization paradigm is proposed as the basic tool for solving this inversion problem and restoring well-posedness. The proposed framework includes (1) a review of 2D regularization, (2) extension of the standard Tikhonov regularization method by allowing space-variant regularization parameters, and (3) further extension of the regularization paradigm by adding multiple data sources for different sensing modalities. The theoretical approach is complemented by developing a regularized hybrid fusion algorithm for solving the early vision problems of edge detection and surface reconstruction. An evaluation of these methods reveals that this new analytical data fusion technique reconstructs a smooth filtered surface in noisy regions while preserving edge characteristics needed for extracting object features. Results indicate the fusion technique is beneficial for combining edge features from different types of sensory data to locate and identify objects of interest.

Paper Details

Date Published: 15 September 1995
PDF: 12 pages
Proc. SPIE 2589, Sensor Fusion and Networked Robotics VIII, (15 September 1995); doi: 10.1117/12.220946
Show Author Affiliations
C. Richardson, Univ. of Tennessee/Knoxville (United States)
Renato A. Salinas Silva, Univ. of Tennessee/Knoxville (United States)
Mongi A. Abidi, Univ. of Tennessee/Knoxville (United States)


Published in SPIE Proceedings Vol. 2589:
Sensor Fusion and Networked Robotics VIII
Paul S. Schenker; Gerard T. McKee, Editor(s)

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