Robust regression and outlier detection
Robust regression and outlier detection
A Method for Registration of 3-D Shapes
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part II
Registering range views of multipart objects
Computer Vision and Image Understanding
Estimating 3-D rigid body transformations: a comparison of four major algorithms
Machine Vision and Applications - Special issue on performance evaluation
Reconstruction of surfaces of revolution from measured points
Computers in Industry
Roundness measurements for discontinuous perimeters via machine visions
Computers in Industry
Model-based registration of front- and backviews of rotationally symmetric objects
Computer Vision and Image Understanding - Registration and fusion of range images
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The development of a complete system of inspection and quality control of manufactured parts requires the coordination of a set of complex processes allowing data acquisition, their dimensional evaluation and their comparison with a reference model. By definition, the parts inspection is the comparison between measurement results and the theoretical surfaces definition in order to check the conformity after manufacturing phase. The automation of this function is currently based on alignment methods of measured points resulting from an acquisition process and these nominal surfaces, in a way that they ''fit best''. The distances between nominal surface and measured points (i.e. form defects) calculated after alignment stages are necessary for the correction of the manufacturing parameters (Henke, Summerhays, Baldwin, Cassou, & Brown, 1999). In this work, a method for automated control based on association of complex surfaces to a cloud points using the Iterative Closest Point (I.C.P.) algorithm for alignment stage is proposed. An industrial application concerning a tooth gear manufactured in our country's tractor engines is presented.