This article presents an algorithm for multiple orien-tation estimation at junctions which can be used as a first step towards a complete description of the junction structure. The algorithm uses the structure tensor ap-proach to determine the orientations of the edges or lines that meet at a junction and then extracts the principal orientations from a histogram of the orientation angles in a circular region around the junction. In contrast to previous solutions it uses only first-order derivatives and is suited for junctions with an arbitrary number of orientations without increasing the runtime. 1
The structure tensor yields an excellent characterization of the local dimensionality and the corres...
The channel representation is a simple yet powerful representation of scalars and vectors. It is esp...
This paper describes a new algorithm for local orientation estimation. The proposed algorithm detect...
Abstract. We present a novel method to detect multimodal regions composed of linear structures and m...
Structure tensors are a common tool for orientation estimation in image processing and computer visi...
The computational cost of conventional filter methods for junction characterization is very high. Th...
this paper is to present an appropriate method for the segmentation of lines at intersections (X-jun...
Structure tensors are a common tool for orientation estimation in image processing and computer visi...
Abstract. We describe three modifications to the structure tensor approach to low-level feature extr...
This paper introduces an operator for the detection of the true location and orientation of corners....
This paper introduces a generic method for the accurate analysis of junctions, relying on a statisti...
Junctions are significant features in images with intensity variation that exhibits multiple orienta...
Junctions are strong cues for understanding the geometry of a scene. In this paper, we consider the ...
International audienceAccurate junction detection and characterization are of primary importance for...
Junction characterization is a very important task since junctions are multi-scalar and multi-orient...
The structure tensor yields an excellent characterization of the local dimensionality and the corres...
The channel representation is a simple yet powerful representation of scalars and vectors. It is esp...
This paper describes a new algorithm for local orientation estimation. The proposed algorithm detect...
Abstract. We present a novel method to detect multimodal regions composed of linear structures and m...
Structure tensors are a common tool for orientation estimation in image processing and computer visi...
The computational cost of conventional filter methods for junction characterization is very high. Th...
this paper is to present an appropriate method for the segmentation of lines at intersections (X-jun...
Structure tensors are a common tool for orientation estimation in image processing and computer visi...
Abstract. We describe three modifications to the structure tensor approach to low-level feature extr...
This paper introduces an operator for the detection of the true location and orientation of corners....
This paper introduces a generic method for the accurate analysis of junctions, relying on a statisti...
Junctions are significant features in images with intensity variation that exhibits multiple orienta...
Junctions are strong cues for understanding the geometry of a scene. In this paper, we consider the ...
International audienceAccurate junction detection and characterization are of primary importance for...
Junction characterization is a very important task since junctions are multi-scalar and multi-orient...
The structure tensor yields an excellent characterization of the local dimensionality and the corres...
The channel representation is a simple yet powerful representation of scalars and vectors. It is esp...
This paper describes a new algorithm for local orientation estimation. The proposed algorithm detect...
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