Low-complexity pruning for accelerating corner detection

• Main Authors: Srikanthan, Thambipillai, Wu, Meiqing, Ramakrishnan, Nirmala, Lam, Siew-Kei
• Other Authors: School of Computer Engineering
• Format: Conference or Workshop Item
• Language: English
• Published: 2013
• Subjects: DRNTU::Engineering::Computer science and engineering
• Online Access: https://hdl.handle.net/10356/102865; http://hdl.handle.net/10220/16922
• Institution: Nanyang Technological University

In this paper, we present a novel and computationally efficient pruning technique to speed up the Shi-Tomasi and Harris corner detectors. The proposed technique quickly prunes non-corners and selects a small corner candidate set by approximating the complex corner measure of Shi-Tomasi and Harris. The actual corner measure is then applied only to the reduced candidate set. Experimental results on the NiOS-II platform show that the proposed technique achieves an average execution time savings of 90% for Shi-Tomasi and 70% for Harris detectors for 500 corners with no loss in accuracy.