Title :
A tensor voting approach for the hierarchical segmentation of 3-D acoustic images
Author :
Tao, Linmi ; Murino, Vittorio ; Medioni, Gérard
Author_Institution :
Dipt. di Informatica, Univ. of Verona, Italy
Abstract :
We present a hierarchical and robust algorithm addressing the problem of filtering and segmentation of three-dimensional acoustic images. This algorithm is based on. the tensor voting approach - a unified computational framework for the inference of multiple salient structures. Unlike most previous approaches, no models or prior information of the underwater environment, nor the intensity information of acoustic images is considered in this algorithm. Salient structures and outlier noisy points are directly clustered in two steps according to both the density and the structural information of input data. Our experimental trials show promising results, very robust despite the low computational complexity.
Keywords :
acoustic signal processing; image segmentation; pattern clustering; smoothing methods; tensors; clustering; density; filtering; hierarchical robust algorithm; image segmentation; multiple salient structure inference; outlier noisy points; tensor voting approach; three-dimensional acoustic images; unified computational framework; Acoustic noise; Clustering algorithms; Filtering algorithms; Image segmentation; Inference algorithms; Robustness; Tensile stress; Underwater acoustics; Voting; Working environment noise;
Conference_Titel :
3D Data Processing Visualization and Transmission, 2002. Proceedings. First International Symposium on
Print_ISBN :
0-7695-1521-4
DOI :
10.1109/TDPVT.2002.1024052