Paper
1 August 1991 Transputer-based parallel algorithms for automatic object recognition
Author Affiliations +
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.
© (1991) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Paolo Giulio Bison, Alberto Braggiotti, and Ermanno G. Grinzato "Transputer-based parallel algorithms for automatic object recognition", Proc. SPIE 1471, Automatic Object Recognition, (1 August 1991); https://doi.org/10.1117/12.44894
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Cited by 1 scholarly publication.
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KEYWORDS
Image processing

Object recognition

Image filtering

Visualization

Infrared imaging

Convolution

Detection and tracking algorithms

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