21 March 2000 Subpixel edge detection for dimensional control by artificial vision
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Dimensional control by artificial vision is becoming a standard tool for industrialists interested in such remote and without contact measurement methods. The expected precision of those systems is largely dependent on camera resolution and high precision requires very costly CCD sensor and frame grabber. A method is proposed which tends to increase significantly the precision of dimensional measurements without increasing the hardware complexity. This algorithm is also quite robust against noisy images such that it could be encountered in real world imaging, a precision of 1/16 pixel can easily be obtained with SNR equals 2 dB. Dimensional control by artificial vision generally involves an edge detection stage in its process, it is this step that we propose to improve. A lot of edge detection techniques with pixel resolution are well known and some of them are designed in order to be robust against image corruption. On the other hand B-spline interpolation methods have been considerably improved and popularized by the signal processing techniques proposed by M. Unser and Al. An algorithm resulting from the merging of these two ideas is proposed in this paper. In this algorithm, the interpolation is prepared by an optimized filtering and by a detection of local maxima of gradient.
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Frederic Truchetet, Frederic Truchetet, Olivier Laligant, Olivier Laligant, } "Subpixel edge detection for dimensional control by artificial vision", Proc. SPIE 3966, Machine Vision Applications in Industrial Inspection VIII, (21 March 2000); doi: 10.1117/12.380066; https://doi.org/10.1117/12.380066


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