Title :
Acoustic Range Image Segmentation by Effective Mean Shift
Author :
Castellani, U. ; Cristani, Matteo ; Murino, Vittorio
Author_Institution :
Dipt. di Informatica, Univ. of Verona, Italy
Abstract :
Image perception in underwater environment is a difficult task for a human operator, and data segmentation becomes a crucial step toward an higher level interpretation and recognition of the observing scenarios. This paper contributes to the related state of the art, by fitting the mean shift clustering paradigm to the segmentation of acoustical range images, providing a segmentation approach in which whatever parameter tuning is absent. Moreover, the method exploits actively the connectivity information provided by the range map, by using reverse projection as acceleration technique. Therefore, the method is able to produce, starting from raw range data, meaningful segmented clouds of points in a fully automatic and efficient fashion.
Keywords :
acoustic imaging; image segmentation; pattern clustering; underwater sound; acceleration technique; acoustic range image segmentation; acoustic signal processing; effective mean shift; image perception; mean shift clustering paradigm; reverse projection paradigm; underwater environment; Acceleration; Acoustic beams; Bandwidth; Humans; Image converters; Image recognition; Image segmentation; Kernel; Signal processing; Underwater acoustics; Acoustic signal processing; Clustering methods; Image segmentation;
Conference_Titel :
Image Processing, 2006 IEEE International Conference on
Conference_Location :
Atlanta, GA
Print_ISBN :
1-4244-0480-0
DOI :
10.1109/ICIP.2006.312769