Vol. 36 (1), pp. 79-90
This paper presents a new method of grouping and matching line segments to recognize objects. We propose a dynamic
programming-based formulation extracting salient line patterns by de5ning a robust and stable geometric representation that
is based on perceptual organizations. As the endpoint proximity, we detect several junctions from image lines. We then search for junction groups by using the collinear constraint between the junctions. Junction groups similar to the model are searched
in the scene, based on a local comparison. A DP-based search algorithm reduces the time complexity for the search of the
model lines in the scene. The system is able to 5nd reasonable line groups in a short time.
This paper presents a new method of grouping and matching line segments to recognize objects. We propose a dynamic
programming-based formulation extracting salient line patterns by de5ning a robust and stable geometric representation that
is based on perceptual organizations. As the endpoint proximity, we detect several junctions from image lines. We then search for junction groups by using the collinear constraint between the junctions. Junction groups similar to the model are searched
in the scene, based on a local comparison. A DP-based search algorithm reduces the time complexity for the search of the
model lines in the scene. The system is able to 5nd reasonable line groups in a short time.