|Table of Contents|

Pavement cracks extraction based on pulse coupled neural network(PDF)

长安大学学报（自然科学版）[ISSN:1006-6977/CN:61-1281/TN]

Issue:
2011年05期
Page:
33-37
Research Field:
Publishing date:
2011-10-20

Info

Title:
Pavement cracks extraction based on pulse coupled neural network
Author(s):
SONG Bei-bei;  WEI Na
School of Information Engineering, Chang'an University, Xi'an 710064, Shaanxi, China
Keywords:
road engineering;  pavement crack;  pulse coupled neural network;  mathematical morphology;  image segment
PACS:
TP183;TP391.41
DOI:
-
Abstract:
Based on the characteristic that pavement crack is much darker than its background, the image segment and crack coarse extraction were realized by adopting pulse coupled neural network model combined with time matrix. Based on the fact that the area of crack is much larger than that of impurities, a new connected region extraction algorithm based on mathematical morphology was proposed. It achieved the fine crack extraction by calculating the pixels number of each region and then adopted threshold method to remove impurities. The results show that the average hit rate and false alarm ratio of the coarse crack extraction method based on pulse coupled neural network are 92.43% and 47.67% respectively, and those of the finer method are 91.1% and 7.68% individually, the accuracy of crack detection is significantly improved. 2 tabs, 4 figs, 8 refs.

References:

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Memo

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Last Update: 2011-10-20