Adaptive Road Crack Detection and Segmentation Using Einstein Operators and ANFIS for Real-Time Applications
Journal Title: Journal of Intelligent Systems and Control - Year 2024, Vol 3, Issue 4
Abstract
A novel approach for road crack detection and segmentation was proposed, incorporating Einstein operators within an Adaptive Neuro-Fuzzy Inference System (ANFIS). This methodology leverages advanced fuzzy aggregation techniques and adaptive mechanisms, combined with dynamic Einstein sum and product operators, to enhance the identification of cracks. The model was designed to effectively manage varying crack intensities, geometries, and noise levels, thereby ensuring high sensitivity and accuracy in real-world road conditions. In the preprocessing stage, robust fuzzification was applied using Gaussian membership functions alongside Einstein operators, which significantly improved feature extraction. The segmentation framework based on ANFIS ensured precise detection and delineation of cracks. The performance of the proposed model was demonstrated through a comparative analysis, showing superior accuracy (95.2%), precision (94.1%), recall (96.4%), and F1-score (95.2%) when compared to state-of-the-art models. Statistical validation was conducted, with p-values < 0.01 for all performance metrics, confirming the reliability and statistical significance of the results. Advanced post-processing techniques, including fuzzy morphological refinement and adjacency matrix-based connectivity analysis, were employed to accurately identify even faint or disconnected cracks. The proposed method exhibits exceptional resilience to environmental variations, offering a reliable and adaptive solution for road maintenance and monitoring. This work highlights the potential of fuzzy logic, statistical validation, and adaptive mechanisms in addressing real-world challenges in road crack detection.
Authors and Affiliations
Ibrar Hussain, Luqman Alam
Keywords
Related Articles
- EP ID EP759848
- DOI https://doi.org/10.56578/jisc030402
- Views 16
- Downloads 0
Robust Speed Control in Nonlinear Electric Vehicles Using H-Infinity Control and the LMI Approach
In this investigation, the robust H∞ control of nonlinear electric vehicles (EVs), powered by permanent magnet synchronous motors (PMSM), was examined. Emphasis was placed on enhancing the accuracy and robustness of the...
Evaluating the Usability and Effectiveness of a Special Education Campus Navigation System for Students with Visual Impairment
This study evaluates the usability and effectiveness of a newly developed special education (SPED) campus navigation system designed for students with visual impairment (SVI) at the Federal College of Education (Special)...
Hybrid Approach Control of Micro-Positioning Stage with a Piezoelectric Actuator
For a class of system with nonlinear hysteresis, this paper presents an adaptive hybrid controller based on the hybrid backstepping-sliding mode, and describes the controller analytically by the LuGre model. Both backste...
Neural Network-Based Control and Active Vibration Mitigation in a Fully-Flexible Arm Space Robot under Elastic Base Influence: A Luenberger Observer Approach
This study explores dynamic simulation and integrated control in a space robotic arm system characterized by a fully-flexible arm and an elastic base. The elastic base is modeled as a lightweight spring, and the modal sh...
A Few Maclaurin Symmetric Mean Aggregation Operators for Spherical Fuzzy Numbers Based on Schweizer-Sklar Operations and Their Use in Artificial Intelligence
One significant benefit of the Maclaurin symmetric mean (MSM) is that it is a generalization of many extend operators and can consider the interrelationships among the multi-input arguments, such as multi-attributes or m...