A new edge detection technique based on detection of normal changes is proposed. Most of the existing range image-based edge detection algorithms base their detection criterion on depth or curvature changes. However, the depth change-based approach does not have keen sensitivity in detecting roof ( or crease ) edges, and the curvature change-based approach suffers from a complicated and tedious principal curvature derivation process. Using normal changes as a detecting criterion, on the other hand, the existence of an edge can be easily detected, even when the change across a boundary is slight. Experimental results using both synthetic and real images demonstrate that the proposed method can efficiently detect both step and roof edges.
CITATION STYLE
Sze, C. J., Liao, H. Y. M., Hung, H. L., Fan, K. C., & Hsieh, J. W. (1997). Multiscale edge detection via normal changes. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1310, pp. 22–29). Springer Verlag. https://doi.org/10.1007/3-540-63507-6_180
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