✦ LIBER ✦

Edge Detector Evaluation Using Empirical ROC Curves

✍ Scribed by Kevin Bowyer; Christine Kranenburg; Sean Dougherty

Book ID: 102967834
Publisher: Elsevier Science
Year: 2001
Tongue: English
Weight: 836 KB
Volume: 84
Category: Article
ISSN: 1077-3142
DOI: 10.1006/cviu.2001.0931

No coin nor oath required. For personal study only.

✦ Synopsis

We demonstrate a method for evaluating edge detector performance based on receiver operating characteristic (ROC) curves. Edge detector output is matched against ground truth to count true positive and false positive edge pixels. A detector's parameter settings are trained to give a best ROC curve on one image and then tested on separate images. We compute aggregate ROC curves based on 1 set of 50 object images and another set of 10 aerial images. We analyze the performance of 11 different edge detectors reported in the literature.

📜 SIMILAR VOLUMES

Evaluating screening questionnaires usin

Evaluating screening questionnaires using receiver Operating Characteristic (ROC) curves from two-phase (double) samples

✍ Giulia Bisoffi; Maria Angela Mazzi; Graham Dunn 📂 Article 📅 2000 🏛 John Wiley and Sons 🌐 English ⚖ 1016 KB

## Abstract The characteristics of psychiatric screening tests (for example, sensitivity, specificity, and AUC – the area under an ROC curve) are frequently assessed using data arising from two‐phase samples. Too often, however, the statistical methods that are used are incorrect. They do not appro