NDLI: Enhanced low-complexity pruning for corner detection

Content Provider	Springer Nature Link
Author	Ramakrishnan, Nirmala Wu, Meiqing Lam, Siew Kei Srikanthan, Thambipillai
Copyright Year	2014
Abstract	Low-complexity corner detection is essential for many real-time computer vision applications that need to be executed on low-cost/low-power embedded platforms such as robots. The widely used Shi–Tomasi and Harris corner detectors become prohibitive in such platforms due to their high computational complexity, which is attributed to the need to apply a complex corner measure on the entire image. In this paper, we introduce a novel and computationally efficient technique to accelerate the Shi–Tomasi and Harris corner detectors. The proposed technique consists of two steps. In the first step, the complex corner measure is replaced with simple approximations to quickly prune away non-corners. In the second step, the complex corner measure is applied to a small corner candidate set obtained after pruning. Evaluations using standard image benchmarks show that the proposed pruning technique achieves up to 75 % speedup on the Nios-II platform, while yielding corners with comparable or better accuracy than the conventional Shi–Tomasi and Harris detectors.
Starting Page	197
Ending Page	213
Page Count	17
File Format	PDF
ISSN	18618200
Journal	Journal of Real-Time Image Processing
Volume Number	12
Issue Number	1
e-ISSN	18618219
Language	English
Publisher	Springer Berlin Heidelberg
Publisher Date	2014-01-28
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Corner detection Low complexity Shi–Tomasi Harris Pruning Image Processing and Computer Vision Multimedia Information Systems Computer Graphics Pattern Recognition Signal, Image and Speech Processing
Content Type	Text
Resource Type	Article
Subject	Information Systems

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