Pattern Spectrum and Multiscale Shape Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Hi-index | 0.00 |
In the present study a granulometry-based method of computing surrogate measure of thickness from gray-level images is introduced. Using Bland-Altman analysis it is demonstrated for a set of 25 μCT images that the difference between surrogate and reference measures of thickness corresponds to some non-zero bias. Analytical formulas derived in this study identify conditions necessary for the equality of surrogate measures of thickness and real thickness. The performance of the proposed method in the presence of image degradation factors (resolution decrease and noise) is tested.