Abstract
Image quality assessment plays an important role in several image processing applications, including data approximation by triangular meshes. The determination of adequate metrics is essential for constructing algorithms that generate high quality models. This paper evaluates a number of different image measures used to refine a given triangular mesh until a specified accuracy is obtained, which are more effective than traditional metrics such as the magnitude of the maximum vertical distance between pairs of corresponding points in the images. Experiments show that a considerable reduction in the triangulation size can be obtained by using more effective criteria for selecting the data points. Several metrics for evaluating the overall quality of the resulting models are also presented and compared.
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Kaick, O.M.v., Pedrini, H. (2006). ASSESSMENT OF IMAGE SURFACE APPROXIMATION ACCURACY GIVEN BY TRIANGULAR MESHES. In: Wojciechowski, K., Smolka, B., Palus, H., Kozera, R., Skarbek, W., Noakes, L. (eds) Computer Vision and Graphics. Computational Imaging and Vision, vol 32. Springer, Dordrecht. https://doi.org/10.1007/1-4020-4179-9_94
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DOI: https://doi.org/10.1007/1-4020-4179-9_94
Publisher Name: Springer, Dordrecht
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