Proceedings ArticleDOI
Use of artificial living system for pavement distress survey
Huiyan Zhang,Q. Wang +1 more
- Vol. 3, pp 2486-2490
TLDR
In this article, a pavement distress detection algorithm is proposed, which includes preprocessing and artificial life algorithm, which is based on a bottom-up synthetic approach and exhibits its emergent properties for distress detection.Abstract:
Automation of pavement surface distress survey is of considerable interest since it facilitates road maintenance. Pavement distress detection algorithm is proposed, which includes preprocessing and artificial life algorithm. In nature, bee population consists of different species of bees. Different species of bees cooperate with others and build combs. The process of building combs is based on a bottom-up structure instead of a top-down centralized controller like expert system and exhibits the emergent properties of bee population. Artificial living system in artificial life algorithm is very similar to bee population. In artificial life algorithm, artificial living system is an artificial population, which is composed of different species of artificial organisms. Artificial living system is based on a bottom-up synthetic approach and exhibits its emergent properties for distress detection. Experimental results demonstrate the proposed method has strong effect on noise removal, oilstains elimination and the rid of dark spots.read more
Citations
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Journal ArticleDOI
Automatic Road Crack Detection and Characterization
TL;DR: A fully integrated system for the automatic detection and characterization of cracks in road flexible pavement surfaces, which does not require manually labeled samples, is proposed to minimize the human subjectivity resulting from traditional visual surveys.
Journal ArticleDOI
Automatic Road Pavement Assessment with Image Processing: Review and Comparison
Sylvie Chambon,Jean Marc Moliard +1 more
TL;DR: An evaluation and comparison protocol which has been designed for evaluating this difficult task—the road pavement crack detection—is introduced and the proposed method is validated, analysed, and compared to a detection approach based on morphological tools.
Proceedings Article
Automatic road crack segmentation using entropy and image dynamic thresholding
TL;DR: This paper presents a novel framework for automatic crack detection and classification using survey images acquired at high driving speeds, using two image databases acquired using professional high speed equipment.
Journal ArticleDOI
A Novel LBP Based Methods for Pavement Crack Detection
Yong Hu,Chun-xia Zhao +1 more
TL;DR: Two optimized architectures of Context-based Adaptive Binary Arithmetic Coding (CABAC) are presented and analysis of implementations for both versions of CABAC is presented.
Journal ArticleDOI
Automatic Pavement Crack Detection Using Texture and Shape Descriptors
TL;DR: Experimental results demonstrated that all cracks are correctly detected by the proposed method, even in a strong texture background or in the surface with uneven illumination, compared with a traditional edge detector such as a Canny operator.
References
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Journal ArticleDOI
Designs and Implementations of Automated Systems for Pavement Surface Distress Survey
TL;DR: A modified approach to collecting and processing surface distress through the use of high-performance digital cameras for the acquisition of surface distress data is presented, in terms of their potential and applicability.
Journal ArticleDOI
Automatic pavement distress detection system
Heng-Da Cheng,M. Miyojim +1 more
TL;DR: A new pavement distress image enhancement algorithm, and a new analysis and classification algorithm that can precisely quantify geometrical and topological parameters, can quickly accept new classification rules for classification, and can estimate the distress severity from the thresholded image are introduced.
Journal ArticleDOI
Optimum design of short journal bearings by artificial life algorithm
TL;DR: In this paper, an enhanced artificial life algorithm for optimum design of short journal bearing was presented. And the optimized results were compared with those of genetic algorithm and successive quadratic programming, and identified the optimizing ability.
Proceedings ArticleDOI
Pavement distress classification using neural networks
TL;DR: The feasibility of using moment invariants and neural networks to classify different types of crack is proven.
Proceedings ArticleDOI
A Markov random field for rectilinear structure extraction in pavement distress image analysis
P. Delagnes,Dominique Barba +1 more
TL;DR: This paper deals with the detection and extraction of poorly contrasted rectilinear structures in textured areas, using a Markov random field model, in the analysis of pavement distress, and more particularly pavement cracks.