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- W2037210182 abstract "Low-level computer vision routines for simple-shaped (rectangular and circular) object recognition have been parallelized and implemented in order to run on a portable, standalone, multiple transputer network. The aim is to provide a flexible, though powerful, computational capability to an open architecture for a multispectral computer vision system applied to both visual and IR bands. Among the developed routines are: image registration routines, rotation, scaling and matching of the images taken from visual band and IR band cameras; filters, linear and NOS filters; transforms, Fourier and Hough. The parallelization of the routines allow them to be run on an arbitrary number of transputers, i.e., on the field with a limited number of transputers for dedicated online tests, or in laboratory for more precise results through intensive offline processing. The main application is the optical survey of masonry structures through the analysis of their surface from the moisture point of view (i.e., old historical buildings in the region of Venice). Recognition of geometrically and physically known objects, like thermal sensors and radiometric and geometric references, represents a crucial initial step toward these tasks." @default.
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- W2037210182 date "1991-08-01" @default.
- W2037210182 modified "2023-09-23" @default.
- W2037210182 title "<title>Transputer-based parallel algorithms for automatic object recognition</title>" @default.
- W2037210182 doi "https://doi.org/10.1117/12.44894" @default.
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