Low-complexity pruning for accelerating corner detection

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. T...

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Main Authors: Srikanthan, Thambipillai, Wu, Meiqing, Ramakrishnan, Nirmala, Lam, Siew-Kei
Other Authors: School of Computer Engineering
Format: Conference Paper
Language:English
Published: 2013
Subjects:
Online Access:https://hdl.handle.net/10356/102865
http://hdl.handle.net/10220/16922
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author Srikanthan, Thambipillai
Wu, Meiqing
Ramakrishnan, Nirmala
Lam, Siew-Kei
author2 School of Computer Engineering
author_facet School of Computer Engineering
Srikanthan, Thambipillai
Wu, Meiqing
Ramakrishnan, Nirmala
Lam, Siew-Kei
author_sort Srikanthan, Thambipillai
collection NTU
description 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.
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spelling ntu-10356/1028652020-05-28T07:18:07Z Low-complexity pruning for accelerating corner detection Srikanthan, Thambipillai Wu, Meiqing Ramakrishnan, Nirmala Lam, Siew-Kei School of Computer Engineering IEEE International Symposium on Circuits and Systems (2012 : Seoul, Korea) Centre for High Performance Embedded Systems DRNTU::Engineering::Computer science and engineering 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. 2013-10-25T07:27:18Z 2019-12-06T21:01:18Z 2013-10-25T07:27:18Z 2019-12-06T21:01:18Z 2012 2012 Conference Paper Wu, M., Ramakrishnan, N., Lam, S.- K., & Srikanthan, T. (2012). Low-complexity pruning for accelerating corner detection. 2012 IEEE International Symposium on Circuits and Systems, pp1684-1687. https://hdl.handle.net/10356/102865 http://hdl.handle.net/10220/16922 10.1109/ISCAS.2012.6271582 en © 2012 IEEE.
spellingShingle DRNTU::Engineering::Computer science and engineering
Srikanthan, Thambipillai
Wu, Meiqing
Ramakrishnan, Nirmala
Lam, Siew-Kei
Low-complexity pruning for accelerating corner detection
title Low-complexity pruning for accelerating corner detection
title_full Low-complexity pruning for accelerating corner detection
title_fullStr Low-complexity pruning for accelerating corner detection
title_full_unstemmed Low-complexity pruning for accelerating corner detection
title_short Low-complexity pruning for accelerating corner detection
title_sort low complexity pruning for accelerating corner detection
topic DRNTU::Engineering::Computer science and engineering
url https://hdl.handle.net/10356/102865
http://hdl.handle.net/10220/16922
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AT wumeiqing lowcomplexitypruningforacceleratingcornerdetection
AT ramakrishnannirmala lowcomplexitypruningforacceleratingcornerdetection
AT lamsiewkei lowcomplexitypruningforacceleratingcornerdetection