Many contemporary works show the interest of the scientific community in measuring the shape of artefacts made by single point incremental forming. In this paper, we will present an algorithm able to detect feature points with a random pattern, check the compatibility of associations exploiting multi-stereo constraints and reject outliers and perform a 3D reconstruction by dense random patterns. The algorithm is suitable for a real-time application, in fact it needs just three images and a synchronous relatively fast processing. The proposed method has been tested on a simple geometry and results have been compared with a coordinate measurement machine acquisition.

Shape measurement system for single point incremental forming (SPIF) manufacts by using trinocular vision and random pattern

Setti, Francesco;Lunardelli, Massimo;Bosetti, Paolo;Bruschi, Stefania;De Cecco, Mariolino
2012

Abstract

Many contemporary works show the interest of the scientific community in measuring the shape of artefacts made by single point incremental forming. In this paper, we will present an algorithm able to detect feature points with a random pattern, check the compatibility of associations exploiting multi-stereo constraints and reject outliers and perform a 3D reconstruction by dense random patterns. The algorithm is suitable for a real-time application, in fact it needs just three images and a synchronous relatively fast processing. The proposed method has been tested on a simple geometry and results have been compared with a coordinate measurement machine acquisition.
Setti, Francesco; Ruggero, Bini; Lunardelli, Massimo; Bosetti, Paolo; Bruschi, Stefania; De Cecco, Mariolino
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/93951
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