Crack is a common form of pavement distress and it carries significant information on the condition of roads. The detection of cracks is essential to perform pavement maintenance and rehabilitation. Many of the highways agencies, in different countries, are still employing conventional, costly and very time consuming techniques which involve direct human intervention and assessment. Although automated recognition has been successfully performed for many pavement distresses, crack detection remains, to this date, a topic where reservations exist. A novel approach to automatically distinguish cracks in digital pavement images is proposed in this paper. The Gabor filter is proven to be a highly potential technique for multidirectional crack detection that was not done previously using the Gabor filter. Image analysis using the Gabor function is directly related to the mammalian visual perception, hence the choice of this method for crack detection. Results reported in this paper concentrate on pavement images with high levels of surface texture that makes crack detection difficult. An initial detection precision of up to 95% has been reported in this paper showing a good promise in the proposed method.
Abstract-Automated systems for road crack detection are extremely important in road maintenance for vehicle safety and traveler's comfort. Emerging cracks in roads need to be detected and accordingly repaired as early as possible to avoid further damage thus reducing rehabilitation cost. In this paper, a robust method for Gabor filter parameters optimization for automatic road crack detection is discussed. Gabor filter has been used in previous literature for similar applications. However, there is a need for automatic selection of optimized Gabor filter parameters due to variation in texture of roads and cracks. The problem of change of background, which in fact is road texture, is addressed through a learning process by using synthetic road crack generation for Gabor filter parameter tuning. Tuned parameters are then tested on real cracks and a thorough quantitative analysis is performed for performance evaluation.
WiMAX base stations are deployed in cellular network to increase the coverage area and capacity. Inter cell interference (ICI) is a major problem in cellular network. Different frequency planning techniques are proposed to handle the ICI effect such as frequency reuse of one (FR-of-1) and fractional frequency reuse (FFR). In this paper, these two types of network deployments are implemented, analyzed, and compared in a grid of 19 base stations, where band adaptive modulation and coding (band-AMC) is used in each cell. Users are randomly distributed in the target cell, and their resource and burst profile selection are determined based on the reported signal to interference plus-noise ratio (SINR). The simulation results proved that FFR shows better performance than FR-of-1 in terms of variety of metrics. FFR enhance the number of served users and resource utilization to 96.42 %, compared to FR-of-1 where only 77.77 % of resources are exploited. The data rate has been increased to 8.280 Mbps under FFR, whereas in FR-of-1 it reaches to 7.277 Mbps. The spectral efficiency in FFR equals to 0.619 Mbps/Hz, whilst it increased to 0.977 Mbps/Hz in FR-of-1, since the latter exploits all the available bandwidth unlike FFR where part of the bandwidth is not used in each cell edge. This work reveals that FFR can enhance the performance of WiMAX base station in an interference environment more than that in FR-of-1, which makes FFR a strong competitor for deploying WiMAX base stations in such environment.
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