An Automatic Detection by Classification of Cracked Pixels or Noncracked Pixels in Road Surface
Author(s) -
Khaddouj Taifi,
Naima Taifi,
Es-said Azougaghe,
Saïd Safi
Publication year - 2021
Publication title -
mathematical problems in engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.262
H-Index - 62
eISSN - 1026-7077
pISSN - 1024-123X
DOI - 10.1155/2021/3151460
Subject(s) - pixel , discrete wavelet transform , artificial intelligence , filter (signal processing) , computer vision , computer science , phase (matter) , wavelet , surface (topology) , image (mathematics) , pattern recognition (psychology) , decomposition , wavelet transform , mathematics , ecology , biology , geometry , chemistry , organic chemistry
Automatic detection and monitoring of the condition of cracks in the road surface are essential elements to ensure road safety and quality of service. A crack detection method based on wavelet transforms (2D-DWT) and Jerman enhancement filter is used. This paper presents different contributions corresponding to the three phases of the proposed system. The first phase presents the contrast enhancement technique to improve the quality of roads surface image. The second phase proposes an effective detection algorithm using discrete wavelet (2D-DWT) with “db8” and two-level sub-band decomposition. Finally, in the third phase, the Jerman enhancement filter is usually used with different parameters of the control response uniformity “ τ ” to enhance for cracks detection. The experimental results in this article provide very powerful results and the comparisons with five existing methods show the effectiveness of the proposed technique to validate the recognition of surface cracks.
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