Year: 2026
Type: article
Abstract: Convex hull computation on large planar point sets is commonly preceded by geometric filtering to reduce input size. Motivated by invariants used in incremental convex hull maintenance, we derive a streaming, certificate-based reduction that discards only points certified interior to the hull. We show that the reduction preserves the exact convex hull and operates in a single streaming pass with only local geometric operations. Experiments on synthetic and real-world datasets demonstrate substantial reduction, retaining between 5% and 11% of input points on average for synthetic distributions and below 1% on large real-world data under typical arrival order.
Source: PLoS ONE
Author: Oswaldo Cadenas
Institution: London South Bank University
Language: English
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,382
OpenAlex ID: W7161709045