# Analysis of ROC for Edge Detectors

arXiv: https://arxiv.org/abs/2305.17820 · HTML: https://mlsanity.com/paper/2305.17820/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 1 of its 9 references that are in the map.
- First posted on arXiv 28 May 2023.

## Builds on (most cited first, 1 of 1)

- [Dense Extreme Inception Network: Towards a Robust CNN Model for Edge Detection](https://mlsanity.com/paper/1909.01955/) (2019)

## Abstract (arXiv)

This paper presents an evaluation of edge detectors using receiver operating characteristic (ROC) analysis on the BIPED dataset. Our study examines the benefits and drawbacks of applying this technique in Matlab. We observed that while ROC analysis is suitable for certain edge filters, but for filters such as Laplacian, Laplacian of Gaussian, and Canny, it presents challenges when accurately measuring their performance using ROC metrics. To address this issue, we introduce customization techniques to enhance the performance of these filters, enabling more accurate evaluation. Through our customization efforts, we achieved improved results, ultimately facilitating a comprehensive assessment of the edge detectors.