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The approach divides the image into rectangular blocks, processing each block in parallel to extract \u201ctriads\u201d (structures representing three interconnected and ordered points). Subsequently, the triads are connected both within each block and between adjacent blocks to form complete, closed contours. The algorithm is composed of three steps, each implemented as CUDA kernels. The main objective of the proposed algorithm is to avoid costly data transfers between the CPU and GPU, while maintaining performance at a level similar to that of the CPU. This objective is, particularly, beneficial when the algorithm is part of industrial workflows with high efficiency requirements.<\/jats:p>","DOI":"10.1007\/s11227-026-08488-4","type":"journal-article","created":{"date-parts":[[2026,4,15]],"date-time":"2026-04-15T11:18:30Z","timestamp":1776251910000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Accelerated border tracking in binary images with GPUs"],"prefix":"10.1007","volume":"82","author":[{"given":"Pedro","family":"Alonso-Jord\u00e1","sequence":"first","affiliation":[]},{"given":"Roberto","family":"D\u00edaz-Cano","sequence":"additional","affiliation":[]},{"given":"Enrique S.","family":"Quintana-Ort\u00ed","sequence":"additional","affiliation":[]},{"given":"Francesc","family":"Folch","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2026,4,15]]},"reference":[{"issue":"05","key":"8488_CR1","doi-asserted-by":"publisher","first-page":"898","DOI":"10.1109\/TPAMI.2010.161","volume":"33","author":"P Arbelaez","year":"2011","unstructured":"Arbelaez P, Maire M, Fowlkes C, Malik J (2011) Contour detection and hierarchical image segmentation. 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