Abstract
We present a novel edge segment detection algorithm that runs real-time and produces high quality edge segments, each of which is a linear pixel chain. Unlike traditional edge detectors, which work on the thresholded gradient magnitude cluster to determine edge elements, our method first spots sparse points along rows and columns called anchors, and then joins these anchors via a smart, heuristic edge tracing procedure, hence the name Edge Drawing (ED). ED produces edge maps that always consist of clean, perfectly contiguous, well-localized, one-pixel wide edges. Edge quality metrics are inherently satisfied without a further edge linking procedure. In addition, ED is also capable of outputting the result in vector form as an array of chain-wise edge segments. Experiments on a variety of images show that ED produces high quality edge maps and runs up to 10% faster than the fastest known implementation of the Canny edge detector (OpenCV's implementation).
Original language | English |
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Pages (from-to) | 862-872 |
Number of pages | 11 |
Journal | Journal of Visual Communication and Image Representation |
Volume | 23 |
Issue number | 6 |
DOIs | |
Publication status | Published - Aug 2012 |
Externally published | Yes |
Funding
This work is partially supported by The Scientific and Technological Research Council of Turkey (TUBITAK) with Grant No. 111E053 .
Funders | Funder number |
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TUBITAK | 111E053 |
Türkiye Bilimsel ve Teknolojik Araştirma Kurumu |
Keywords
- Edge detection
- Edge quality metrics
- Edge segment detection
- Real-time imaging