LINE SEGMENT MATCHING ALGORITHM BASED ON FEATURE GROUPING AND LBD DESCRIPTOR

Abstract

Abstract. This paper proposes a line-matching algorithm based on feature grouping and a line band descriptor (LBD) to address the insufficient reliability of individual line descriptors for line matching. First, the algorithm generates line-pairs according to geometrical relationships such as the distances and angles between line segments extracted from a single image. Subsequently, the algorithm employs the epipolar line of intersection between two lines in a reference line-pair to constrain candidate pairs corresponding to the reference line-pair. Thereafter, each line in the reference line-pair is considered individually, and its support region and the corresponding support region of each candidate line in the candidate pairs are established, following which an affine transformation is used for unifying the sizes of the reference support region and the candidate support region. Moreover, the LBD descriptor is then used for describing the reference and candidate lines. The Euclidean distances between the reference line and each candidate line descriptors are calculated, and the nearest neighbor distance ratio (NNDR) is used as a criterion for determining the final matching. Finally, the one-to-many and many-to-one line correspondences in matching results are transformed into one-to-one line correspondences by fitting multiple lines to the new line; simultaneously, incorrect matches are eliminated. The experimental results show that the proposed algorithm yields reliable line-matching performance for close-range images.