Hyperspectral Image-Based Night-Time Vehicle Light Detection Using Spectral Normalization and Distance Mapper for Intelligent Headlight Control

Kim, Hee-Kang; Kwon, Soon Jae; Kim, Sungho

doi:10.3390/s16071058

Cited by 5 publications

(3 citation statements)

References 33 publications

(36 reference statements)

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“…Another aspect is estimation of the distance between vehicles using algorithms for detecting vehicle lights at night and normalizing the angle of their lighting [20]. Subsequent systems are also based on the omnidirectional monitoring of the area around the vehicle [21], which is extremely important on car roads, but not always effective for other applications.…”

Section: Video Materialsmentioning

confidence: 99%

Low Complexity Lane Detection Methods for Light Photometry System

et al. 2021

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The aim of the paper was to analyze effective solutions for accurate lane detection on the roads. We focused on effective detection of airport runways and taxiways in order to drive a light-measurement trailer correctly. Three techniques for video-based line extracting were used for specific detection of environment conditions: (i) line detection using edge detection, Scharr mask and Hough transform, (ii) finding the optimal path using the hyperbola fitting line detection algorithm based on edge detection and (iii) detection of horizontal markings using image segmentation in the HSV color space. The developed solutions were tuned and tested with the use of embedded devices such as Raspberry Pi 4B or NVIDIA Jetson Nano.

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Section: Video Materialsmentioning

confidence: 99%

Low Complexity Lane Detection Methods for Light Photometry System

et al. 2021

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“…Classify through this angle. SAM kernel is widely used in hyperspectral imaging because it can quickly measure and classify the similarity of spectral angles [27][28][29][30]. The equation of SAM is shown in (3).…”

Section: Multi-class Support Vector Machinementioning

confidence: 99%

Rapid Foreign Object Detection System on Seaweed Using VNIR Hyperspectral Imaging

Kwak

Son

Park

et al. 2021

Sensors

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The consumption of seaweed is increasing year by year worldwide. Therefore, the foreign object inspection of seaweed is becoming increasingly important. Seaweed is mixed with various materials such as laver and sargassum fusiforme. So it has various colors even in the same seaweed. In addition, the surface is uneven and greasy, causing diffuse reflections frequently. For these reasons, it is difficult to detect foreign objects in seaweed, so the accuracy of conventional foreign object detectors used in real manufacturing sites is less than 80%. Supporting real-time inspection should also be considered when inspecting foreign objects. Since seaweed requires mass production, rapid inspection is essential. However, hyperspectral imaging techniques are generally not suitable for high-speed inspection. In this study, we overcome this limitation by using dimensionality reduction and using simplified operations. For accuracy improvement, the proposed algorithm is carried out in 2 stages. Firstly, the subtraction method is used to clearly distinguish seaweed and conveyor belts, and also detect some relatively easy to detect foreign objects. Secondly, a standardization inspection is performed based on the result of the subtraction method. During this process, the proposed scheme adopts simplified and burdenless calculations such as subtraction, division, and one-by-one matching, which achieves both accuracy and low latency performance. In the experiment to evaluate the performance, 60 normal seaweeds and 60 seaweeds containing foreign objects were used, and the accuracy of the proposed algorithm is 95%. Finally, by implementing the proposed algorithm as a foreign object detection platform, it was confirmed that real-time operation in rapid inspection was possible, and the possibility of deployment in real manufacturing sites was confirmed.

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“…In the case of light sources, the same CCT can be implemented in various ways, and metamerism can be affected accordingly. In particular, the use of a spectral camera can be a method to analyze the characteristics of light sources by wavelength band, and there is a case of using a hyperspectral camera in the image recognition field to distinguish between the street lights and the headlights of vehicles [31].…”

Section: Limitations Of This Study and Further Studiesmentioning

confidence: 99%

A Study on the Night Visibility Evaluation Method of Color Temperature Convertible Automotive Headlamps Considering Weather Conditions

Kang

Kwon

2021

Applied Sciences

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This study evaluated a method of applying color temperature convertible headlamps to improve driving safety in adverse weather conditions such as fog and rain during night driving. The concept of color temperature convertible headlamps is to improve the driver’s visibility by driving with a color temperature of 6000 K on a clear night and switching to a color temperature of 3000 K with better light transmittance at night in adverse weather. Through this study, a method for evaluating the night visibility related to such color temperature convertible headlamps under bad weather at night was suggested. To this end, a method of using a facility that can implement weather conditions such as fog and rain was proposed, and evaluation conditions according to the climatic conditions and the distance of pedestrian targets were set and actual tests were conducted.

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Hyperspectral Image-Based Night-Time Vehicle Light Detection Using Spectral Normalization and Distance Mapper for Intelligent Headlight Control

Cited by 5 publications

References 33 publications

Low Complexity Lane Detection Methods for Light Photometry System

Low Complexity Lane Detection Methods for Light Photometry System

Rapid Foreign Object Detection System on Seaweed Using VNIR Hyperspectral Imaging

A Study on the Night Visibility Evaluation Method of Color Temperature Convertible Automotive Headlamps Considering Weather Conditions

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