Interest Point Detection Method Based on Dilation Operation

doi:10.3969/j.issn.1000-1093.2017.10.021

Abstract

Abstract: An interest point detection method based on dilation operation (DMDO) is proposed to improve the efficiency and accuracy of interest point detection, in which binarization is used to filter the noise, and the dilation operation is used to replace the clustering approach to enhance the efficiency of algorithm. DMDO is applied to two datasets of open space-AMSA and IMIS3Days. Compared to Density-Based Spatial Clustering of Applications with Noise (DBSCAN) , the accuracy of DMDO is increased by 17.94% on dataset AMSA, and by 19.98% on dataset IMIS3Days, while the efficiency is improved by 6.63 times on dataset AMSA, and by 9.13 times on dataset IMIS3Days. Compared to Ordering Point To Identify the Cluster Structure (OPTICS), the accuracy of DMDO is increased by 20.04% on dataset AMSA, and by 16.60% on dataset IMIS3Days, while the efficiency is improved by 14.61 times on dataset AMSA, and by 42.19 times on dataset IMIS3Days. Experimental results demonstrate that, compared with traditional methods, DMDO has higher accuracy with less time overhead. DMDO is applicable to detect the interest points in the era of big data. Key

Key words: informationprocessingtechnology, trajectorydatamining, interestpointdetection, dilationoperation, openspace

CLC Number:

TP181

WANG Qing， DING Chi-biao， FU Kun， REN Wen-juan. Interest Point Detection Method Based on Dilation Operation[J]. Acta Armamentarii, 2017, 38(10): 2041-2047.

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第38卷第10期2017 年10月兵工学报ACTA
ARMAMENTARIIVol.38No.10Oct. 2017

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