TY - JOUR
T1 - Estimation of multiple orientations at corners and junctions
AU - Mota, Cicero
AU - Stuke, Ingo
AU - Aach, Til
AU - Barth, Erhardt
PY - 2004/12/1
Y1 - 2004/12/1
N2 - Features like junctions and corners are a rich source of information for image understanding. We present a novel theoretical framework for the analysis of such 2D features in scalar and multispectral images. We model the features as occluding superpositions of two different orientations and derive a new constraint equation based on the tensor product of two directional derivatives. The eigensystem analysis of a 3 x 3-tensor then provides the so-called mixed-orientation parameters (MOP) vector that encodes the two orientations uniquely, but only implicitly. We then show how to separate the MOP vector into the two orientations by finding the roots of a second-order polynomial. Based on the orientations, the occluding boundary and the center of the junction are easily determined. The results confirm the validity, robustness, and accuracy of the approach.
AB - Features like junctions and corners are a rich source of information for image understanding. We present a novel theoretical framework for the analysis of such 2D features in scalar and multispectral images. We model the features as occluding superpositions of two different orientations and derive a new constraint equation based on the tensor product of two directional derivatives. The eigensystem analysis of a 3 x 3-tensor then provides the so-called mixed-orientation parameters (MOP) vector that encodes the two orientations uniquely, but only implicitly. We then show how to separate the MOP vector into the two orientations by finding the roots of a second-order polynomial. Based on the orientations, the occluding boundary and the center of the junction are easily determined. The results confirm the validity, robustness, and accuracy of the approach.
UR - http://www.scopus.com/inward/record.url?scp=35048866490&partnerID=8YFLogxK
U2 - 10.1007/978-3-540-28649-3_20
DO - 10.1007/978-3-540-28649-3_20
M3 - Journal articles
AN - SCOPUS:35048866490
SN - 0302-9743
VL - 3175
SP - 163
EP - 170
JO - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
JF - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ER -