English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

In this paper, we propose an original manner to employ a tangential coveralgorithm - minDSS - in order to geometrically reconstruct noisy digitalcontours. To do so, we exploit the representation of graphical objects bymaximal primitives we have introduced in previous works. By calculatingmulti-scale and irregular isothetic representations of the contour, we obtained1-D (one-dimensional) intervals, and achieved afterwards a decomposition intomaximal line segments or circular arcs. By adapting minDSS to this sparse andirregular data of 1-D intervals supporting the maximal primitives, we are nowable to reconstruct the input noisy objects into cyclic contours made of linesor arcs with a minimal number of primitives. In this work, we explain our novelcomplete pipeline, and present its experimental evaluation by considering bothsynthetic and real image data. We also show that this is a robust approach,with respect to selected references from state-of-the-art, and by considering amulti-scale noise evaluation process.

Robust reconstructions by multi-scale/irregular tangential covering