Lane Line Edge Detection Based on Improved Adaptive Canny Algorithm

Xiao, Zhang; Chen, Fuen

doi:10.1088/1742-6596/1549/2/022131

Cited by 9 publications

(2 citation statements)

References 3 publications

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“…Blind Spot is area behind the car which will not be available either from the front view mirror or from the rear view mirror (10) (11) . The vehicle's BSD autonomy is provided by ultrasonic sensors.…”

Section: Blind Spot Detection and Alerting Systemmentioning

confidence: 99%

Advanced Driving Assistance System for Cars Using Raspberry Pi

Ramachandra¹,

Viswanatha²,

Suhas³

et al. 2022

IJST

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Objectives : Hardware implementation of advanced driving assistance system which can be able to identify i). Lane detection and assist system. ii). Blind spot detection and warning system (BSDW). iii). Forward collision and warning system (FCWS). iv). Pedestrian detection system. The primary goal of the developed system is to identify the above features in order to prevent accidents on the road and ensure pedestrian safety. Methods: The suggested method uses a canny edges detection algorithm is used to detect road edges. The input to this system is images captured by the camera with the help of the Open CV library a python image processing algorithm is created that tracks the lane. Histogram of Orientation (HOG) using the sliding window method is used for pedestrian detection. The control unit for the proposed system is Raspberry Pi module 3B, JSN-SR04T ultrasonic sensor and HC-SR04 ultrasonic sensor has been used for (BSDW) system and (FCWS) respectively. Findings: Results demonstrate that the suggested technique can accurately recognize both straight and curved lanes using edge detection algorithm, and also able to identify vehicles in Blind spot area. Novelty: This technology has a high demand in the automotive industry and the system can be implemented in all the future cars which can able to reduce the accident rates.

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Section: Blind Spot Detection and Alerting Systemmentioning

confidence: 99%

Advanced Driving Assistance System for Cars Using Raspberry Pi

Ramachandra¹,

Viswanatha²,

Suhas³

et al. 2022

IJST

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show abstract

“…A unique approach has been employed for edge extraction, addressing the influence of random noise [ 7 ]. An adaptive median filter was used for Canny edge detection [ 8 ]. The Sobel edge detection results have been refined by applying the WNNM algorithm for denoising in noisy environments [ 9 ].…”

Section: Introductionmentioning

confidence: 99%

Intelligent Tapping Machine: Tap Geometry Inspection

Lin,

Chen,

Lien

2023

Sensors

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Currently, the majority of industrial metal processing involves the use of taps for cutting. However, existing tap machines require relocation to specialized inspection stations and only assess the condition of the cutting edges for defects. They do not evaluate the quality of the cutting angles and the amount of removed material. Machine vision, a key component of smart manufacturing, is commonly used for visual inspection. Taps are employed for processing various materials. Traditional tap replacement relies on the technician’s accumulated empirical experience to determine the service life of the tap. Therefore, we propose the use of visual inspection of the tap’s external features to determine whether replacement or regrinding is needed. We examined the bearing surface of the tap and utilized single images to identify the cutting angle, clearance angle, and cone angles. By inspecting the side of the tap, we calculated the wear of each cusp. This inspection process can facilitate the development of a tap life system, allowing for the estimation of the durability and wear of taps and nuts made of different materials. Statistical analysis can be employed to predict the lifespan of taps in production lines. Experimental error is 16 μm. Wear from tapping 60 times is equivalent to 8 s of electric grinding. We have introduced a parameter, thread removal quantity, which has not been proposed by anyone else.

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Cross-type image similarity measurement

Yue

Jiang

et al. 2022

SIViP

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Lane Line Edge Detection Based on Improved Adaptive Canny Algorithm

Cited by 9 publications

References 3 publications

Advanced Driving Assistance System for Cars Using Raspberry Pi

Advanced Driving Assistance System for Cars Using Raspberry Pi

Intelligent Tapping Machine: Tap Geometry Inspection

Cross-type image similarity measurement

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