Pattern Recognition Letters
Structured Highlight Inspection of Specular Surfaces
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shape from shading
Automated Quality Control for Micro-Technology Components Using a Depth from Focus Approach
SSIAI '02 Proceedings of the Fifth IEEE Southwest Symposium on Image Analysis and Interpretation
On defocus, diffusion and depth estimation
Pattern Recognition Letters
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Labeling and marking industrial manufactured objects gets increasingly important nowadays because of novel material properties and plagiarism. As part of the Collaborative Research Center 653 which investigates micro-structured metallic surfaces for inherent mechanical data storage, we research into a stable and reliable optical readout of the written data. Since this comprises a qualitative surface reconstruction, we use directed illumination to make the micro structures visible. Then we apply a spectral analysis to obtain image partitioning and perform signal tracking enhanced by a customized Hidden Markov Model. In this paper, we derive the algorithms used and demonstrate reading data from a surface with 1.6kbit/cm2 from a micro-structured groove which varies by only 3μ m in depth (thus a "scratch"). We demonstrate the system's robustness with experiments with real and artificially-rendered surfaces.