CVOct 11, 2021

An automated threshold Edge Drawing algorithm

arXiv:2110.05119v1
Originality Synthesis-oriented
AI Analysis

This work addresses the costly and complex task of parameter tuning in edge detection for computer vision applications, but it is incremental as it builds on an existing algorithm.

The paper tackled the problem of manual parameter selection in edge detection by introducing an automated threshold step into the Edge Drawing algorithm, resulting in improved edge-maps as shown through visual and statistical results.

Parameter choosing in classical edge detection algorithms can be a costly and complex task. Choosing the correct parameters can improve considerably the resulting edge-map. In this paper we present a version of Edge Drawing algorithm in which we include an automated threshold choosing step. To better highlight the effect of this additional step we use different first order operators in the algorithm. Visual and statistical results are presented to sustain the benefits of the proposed automated threshold scheme.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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