Euclidean Distance Transform of 3D Images on L.A.R.P.B.S. model - Diwan, Piyush
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EDT of 2-D and 3-D images is one of the useful tools in various image processing algorithms. It is one of the basic operations in image processing and computer vision fields and essentially used in expanding, shrinking, thinning, segmentation, clustering and computing of images, object reconstruction, etc. It converts a binary image consisting of black and white voxels to a representation where each voxel has the Euclidean distance of the nearest black voxel. The objective of this work is to derive, implement and analyze an efficient time-optimal and scalable algorithm for EDT computation of…mehr

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Produktbeschreibung
EDT of 2-D and 3-D images is one of the useful tools in various image processing algorithms. It is one of the basic operations in image processing and computer vision fields and essentially used in expanding, shrinking, thinning, segmentation, clustering and computing of images, object reconstruction, etc. It converts a binary image consisting of black and white voxels to a representation where each voxel has the Euclidean distance of the nearest black voxel. The objective of this work is to derive, implement and analyze an efficient time-optimal and scalable algorithm for EDT computation of 3-D images, on a recently proposed multiprocessor architecture, known as Linear Array with Reconfigurable Pipe-lined Bus System (LARPBS).
Autorenporträt
The author has been working in IT industry since last 3 years. He has worked for Symantec Corporation in Storage domain and I-Flapp Technologies in application portability domain. He has pursued M.Tech. from Indian Institute Of Technology,Roorkee(India) and B.E. from Government Engineering College,Raipur(India) in Computer Science and Engineering.