Abstract
Digital image correlation method using artificial neural networks for subpixel displacement measurement is described in this paper. The integer pixel accuracy displacement is calculated based on cross correlation between subimages from undeformed and deformed images by two-dimensional discrete Fourier transform. Subpixel accuracy is obtained by training ANNs. Computer-simulated images are then used to verify this method. Results indicate it can obtain similar accuracies compared with other subpixel algorithms, but the ANN approach has the advantage that it can obtain subpixel displacement faster without knowledge of the analytical form of correlation coefficient of the interested point and its neighbours. Then the effects of speckle size, noise of images are studied. An optimal speckle size for optimal accuracy and the performance of the noise robustness are obtained.
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Liu, Xy., Tan, Qc., Li, Rl. (2010). Study on Digital Image Correlation Using Artificial Neural Networks for Subpixel Displacement Measurement. In: Zeng, Z., Wang, J. (eds) Advances in Neural Network Research and Applications. Lecture Notes in Electrical Engineering, vol 67. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12990-2_46
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DOI: https://doi.org/10.1007/978-3-642-12990-2_46
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