Improving the Matching Rate of Line Feature by Using Dynamic Simplification
Vector line feature matching is one of the hot research in the field of spatial data matching. This paper proposes a method of improving the accuracy of line feature matching based on dynamic simplification. Firstly, use the square root law to respectively determine the numeric ranges of the simplif...
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doaj-90c8f2e0842d40e18016c0bd35a573162020-11-24T23:02:30ZzhoSurveying and Mapping PressActa Geodaetica et Cartographica Sinica1001-15951001-15952016-04-0145448649310.11947/j.AGCS.2016.2015007420160414Improving the Matching Rate of Line Feature by Using Dynamic SimplificationCHEN Jingnan0QIAN Haizhong1WANG Xiao2HE Haiwei3HU Huiming4Institute of Geographic Spatial Information, Information Engineering University, Zhengzhou 450000, ChinaAbstractInstitute of Geographic Spatial Information, Information Engineering University, Zhengzhou 450000, ChinaAbstractInstitute of Geographic Spatial Information, Information Engineering University, Zhengzhou 450000, ChinaAbstractInstitute of Geographic Spatial Information, Information Engineering University, Zhengzhou 450000, ChinaAbstractInstitute of Geographic Spatial Information, Information Engineering University, Zhengzhou 450000, ChinaAbstractVector line feature matching is one of the hot research in the field of spatial data matching. This paper proposes a method of improving the accuracy of line feature matching based on dynamic simplification. Firstly, use the square root law to respectively determine the numeric ranges of the simplification thresholds for the two matching line features; then, let the threshold change by a certain step within this range, and simplify the line features separately. After every simplification is completed, the matching similarity is recalculated and replaced by a higher value so as to attain the maximum similarity. Finally, compare the maximum similarity with the matching threshold to judge if the two line features match. This algorithm is essentially a process which adopts the dynamic simplification to drive the dynamic matching. The dynamic simplification can retain line's main morphological feature, in this way the impact of local details on matching algorithm decreases, accordingly the matching accuracy is improved. The validity and universality of the presented method is proved through experiments and comparative analysis.http://html.rhhz.net/CHXB/html/2016-4-486.htmline feature matchingdynamic simplificationsquare root law |
collection |
DOAJ |
language |
zho |
format |
Article |
sources |
DOAJ |
author |
CHEN Jingnan QIAN Haizhong WANG Xiao HE Haiwei HU Huiming |
spellingShingle |
CHEN Jingnan QIAN Haizhong WANG Xiao HE Haiwei HU Huiming Improving the Matching Rate of Line Feature by Using Dynamic Simplification Acta Geodaetica et Cartographica Sinica line feature matching dynamic simplification square root law |
author_facet |
CHEN Jingnan QIAN Haizhong WANG Xiao HE Haiwei HU Huiming |
author_sort |
CHEN Jingnan |
title |
Improving the Matching Rate of Line Feature by Using Dynamic Simplification |
title_short |
Improving the Matching Rate of Line Feature by Using Dynamic Simplification |
title_full |
Improving the Matching Rate of Line Feature by Using Dynamic Simplification |
title_fullStr |
Improving the Matching Rate of Line Feature by Using Dynamic Simplification |
title_full_unstemmed |
Improving the Matching Rate of Line Feature by Using Dynamic Simplification |
title_sort |
improving the matching rate of line feature by using dynamic simplification |
publisher |
Surveying and Mapping Press |
series |
Acta Geodaetica et Cartographica Sinica |
issn |
1001-1595 1001-1595 |
publishDate |
2016-04-01 |
description |
Vector line feature matching is one of the hot research in the field of spatial data matching. This paper proposes a method of improving the accuracy of line feature matching based on dynamic simplification. Firstly, use the square root law to respectively determine the numeric ranges of the simplification thresholds for the two matching line features; then, let the threshold change by a certain step within this range, and simplify the line features separately. After every simplification is completed, the matching similarity is recalculated and replaced by a higher value so as to attain the maximum similarity. Finally, compare the maximum similarity with the matching threshold to judge if the two line features match. This algorithm is essentially a process which adopts the dynamic simplification to drive the dynamic matching. The dynamic simplification can retain line's main morphological feature, in this way the impact of local details on matching algorithm decreases, accordingly the matching accuracy is improved. The validity and universality of the presented method is proved through experiments and comparative analysis. |
topic |
line feature matching dynamic simplification square root law |
url |
http://html.rhhz.net/CHXB/html/2016-4-486.htm |
work_keys_str_mv |
AT chenjingnan improvingthematchingrateoflinefeaturebyusingdynamicsimplification AT qianhaizhong improvingthematchingrateoflinefeaturebyusingdynamicsimplification AT wangxiao improvingthematchingrateoflinefeaturebyusingdynamicsimplification AT hehaiwei improvingthematchingrateoflinefeaturebyusingdynamicsimplification AT huhuiming improvingthematchingrateoflinefeaturebyusingdynamicsimplification |
_version_ |
1725636438100279296 |