Details

Autor(en) / Beteiligte

• Wang, Mingzhe
• Sun, Changming
• Sowmya, Arcot

Titel

Efficient corner detection based on corner enhancement filters

Ist Teil von

• Digital signal processing, 2022-04, Vol.122, p.103364, Article 103364

Ort / Verlag

Elsevier Inc

Erscheinungsjahr

2022

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• Multi-scale analysis based corner detection algorithms yield impressive performance, however, they are not efficient and not suitable for real-time computer vision tasks. The classical corner detection algorithms including FAST and Harris are computationally efficient, but their detection accuracy and repeatability are insufficient. This paper describes a novel fast corner detector with a simple architecture and high parallel computing characteristics. In order to simplify the corner detection architecture and improve its parallel computing performance, a new type of filter is proposed that can enhance corners and suppress edges and noise simultaneously. Then a novel efficient corner detector is proposed, which can be adapted to achieve real-time detection in hardware. Experimental results show that, with a very low computational cost and simple architecture, the proposed detector can achieve or even exceed the detection accuracy of multi-scale analysis based detectors. Its repeatability is similar to multi-scale analysis based detectors and clearly higher than other types of corner detectors. Therefore, it is potentially useful as an efficient corner detector for computer vision applications especially for portable real-time tasks. •An efficient corner detector with a relatively high performance is proposed.•The concept of enhancing corners and suppressing edges with filters is novel.•The proposed detector can be adapted for real-time corner detection on FPGA hardware.