2011/06/30 by Guillaume Noyel, Jesús Angulo, Jesus Angulo +1 · 7 citations
Computer Science · Engineering · Mathematics · #Advanced Image and Video Retrieval Techniques #Algorithm #Combinatorics #Computation #Computer science #Computer vision #Geodesic #Geodesic map #Geometry #Image Retrieval and Classification Techniques #Mathematics #Medical Image Segmentation Techniques #Pixel #Point (geometry) #Redundancy (engineering) #Topology (electrical circuits) #cs.DM #eess.IV
paper · pdf · doi:10.5566/ias.v30.p101-109
published in Image Analysis & Stereology 30(2), 101 (Slovenian Society for Stereology and Quantitative Image Analysis)
openalex publication_date 2011/06/30 · arxiv created 2020/07/31 · arxiv updated 2020/08/03 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
Computing an array of all pairs of geodesic distances between the pixels of an image is time consuming. In the sequel, we introduce new methods exploiting the redundancy of geodesic propagations and compare them to an existing one. We show that our method in which the source point of geodesic propagations is chosen according to its minimum number of distances to the other points, improves the previous method up to 32 % and the naive method up to 50 % in terms of reduction of the number of operations.