Image Based Automatic Road Surface Crack Detection for Achieving Smooth Driving on Deformed Roads

Premachandra, Chinthaka; Waruna, H.; Premachandra, H. Waruna H.; Parape, Chandana Dinesh

doi:10.1109/smc.2013.686

Cited by 18 publications

(7 citation statements)

References 5 publications

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“…In [48,49] is presented an image based automatic road crack detection method, in which image areas belonging to normal road surface and crack road surface are distinguished by using image sample variance (where a sample is a window of the image), and only image samples belonging to crack road surface are further elaborated for crack detection, improving also the accuracy of detection [49]. The variance is calculated for the set of sample windows that constitute the image, and a threshold is applied to detect the samples that include cracks.…”

Section: Rationalmentioning

confidence: 99%

A pre‐processing technique to decrease inspection time in glass tube production lines

Vitis

Foglia

Prete

2021

IET Image Processing

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In case of glass tube for pharmaceutical applications, high-quality defect detection is made via inspection systems based on computer vision. The processing must guarantee realtime inspection and meet increasing rate and quality requirements. Defect detection in glass tubes is complicated by aspects that hamper the efficiency of state-of-the-art techniques. This paper presents a pre-processing algorithm which excludes portions of the image where defects are surely absent. The approach decreases the time for defect detection and classification phases (any detection algorithm can be applied), as they are applied only in high-probability candidate sub-image. We derive a methodology to get robust values of algorithm's parameters during production. The algorithm relies on detrended standard deviation and double threshold hysteresis, which solve issues related to the misalignment between illuminator and acquisition camera, and enable a robust detection despite rotation, vibration, and irregularities of tubes. We consider Canny, MAGDDA, and Niblack algorithms. The solution keeps the detection quality of such algorithms and reaches a 4.69× throughput gain. It represents a methodology to obtain defect detection in timeconstrained environments through a software-only approach, and can be exploited in parallel/accelerated solutions and in contexts where a linear camera is utilized on both flat and uneven surfaces.This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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Section: Rationalmentioning

confidence: 99%

A pre‐processing technique to decrease inspection time in glass tube production lines

Vitis

Foglia

Prete

2021

IET Image Processing

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“…In the traditional approach, various method were studied to identify defects for various application. In [29], Chinthaka et al presented an image-based automatic road crack detection framework for achieving smooth driving on deformed roads. Otsu's binarization, a discriminant analysis method, was employed for crack extraction from crack images of each sample.…”

Section: Literature Surveymentioning

confidence: 99%

Drain Structural Defect Detection and Mapping Using AI-Enabled Reconfigurable Robot Raptor and IoRT Framework

Palanisamy

Elara

Semwal

et al. 2021

Sensors

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Human visual inspection of drains is laborious, time-consuming, and prone to accidents. This work presents an AI-enabled robot-assisted remote drain inspection and mapping framework using our in-house developed reconfigurable robot Raptor. The four-layer IoRT serves as a bridge between the users and the robots, through which seamless information sharing takes place. The Faster RCNN ResNet50, Faster RCNN ResNet101, and Faster RCNN Inception-ResNet-v2 deep learning frameworks were trained using a transfer learning scheme with six typical concrete defect classes and deployed in an IoRT framework remote defect detection task. The efficiency of the trained CNN algorithm and drain inspection robot Raptor was evaluated through various real-time drain inspection field trials using the SLAM technique. The experimental results indicate that robot’s maneuverability was stable, and its mapping and localization were also accurate in different drain types. Finally, for effective drain maintenance, the SLAM-based defect map was generated by fusing defect detection results in the lidar-SLAM map.

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“…• Detecting Road Surface and Lanes: As for road surface detection, the discriminant analysis (DA) is presented to characterize the road crack [201], [202]. This can provide a threshold for classification according to the road texture and color in images.…”

Section: B Autonomous Drivingmentioning

confidence: 99%

Importance of Small Probability Events in Big Data: Information Measures, Applications, and Challenges

et al. 2019

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In many applications (e.g., anomaly detection and security systems) of smart cities, rare events dominate the importance of the total information on big data collected by the Internet of Things (IoT). That is, it is pretty crucial to explore the valuable information associated with the rare events involved in minority subsets of the voluminous amounts of data. To do so, how to effectively measure the information with the importance of the small probability events from the perspective of information theory is a fundamental question. This paper first makes a survey of some theories and models with respect to importance measures and investigates the relationship between subjective or semantic importance and rare events in big data. Moreover, some applications for message processing and data analysis are discussed in the viewpoint of information measures. In addition, based on rare events detection, some open challenges related to information measures, such as smart cities, autonomous driving, and anomaly detection in the IoT, are introduced which can be considered as future research directions.

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Image Based Automatic Road Surface Crack Detection for Achieving Smooth Driving on Deformed Roads

Cited by 18 publications

References 5 publications

A pre‐processing technique to decrease inspection time in glass tube production lines

A pre‐processing technique to decrease inspection time in glass tube production lines

Drain Structural Defect Detection and Mapping Using AI-Enabled Reconfigurable Robot Raptor and IoRT Framework

Importance of Small Probability Events in Big Data: Information Measures, Applications, and Challenges

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