Hyperspectral Image-Based Night-Time Vehicle Light Detection Using Spectral Normalization and Distance Mapper for Intelligent Headlight Control
This paper proposes a vehicle light detection method using a hyperspectral camera instead of a Charge-Coupled Device (CCD) or Complementary metal-Oxide-Semiconductor (CMOS) camera for adaptive car headlamp control. To apply Intelligent Headlight Control (IHC), the vehicle headlights need to be detec...
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| Format: | Article |
| Language: | English |
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MDPI AG
2016-07-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | http://www.mdpi.com/1424-8220/16/7/1058 |
| _version_ | 1798025447775141888 |
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| author | Heekang Kim Soon Kwon Sungho Kim |
| author_facet | Heekang Kim Soon Kwon Sungho Kim |
| author_sort | Heekang Kim |
| collection | DOAJ |
| description | This paper proposes a vehicle light detection method using a hyperspectral camera instead of a Charge-Coupled Device (CCD) or Complementary metal-Oxide-Semiconductor (CMOS) camera for adaptive car headlamp control. To apply Intelligent Headlight Control (IHC), the vehicle headlights need to be detected. Headlights are comprised from a variety of lighting sources, such as Light Emitting Diodes (LEDs), High-intensity discharge (HID), and halogen lamps. In addition, rear lamps are made of LED and halogen lamp. This paper refers to the recent research in IHC. Some problems exist in the detection of headlights, such as erroneous detection of street lights or sign lights and the reflection plate of ego-car from CCD or CMOS images. To solve these problems, this study uses hyperspectral images because they have hundreds of bands and provide more information than a CCD or CMOS camera. Recent methods to detect headlights used the Spectral Angle Mapper (SAM), Spectral Correlation Mapper (SCM), and Euclidean Distance Mapper (EDM). The experimental results highlight the feasibility of the proposed method in three types of lights (LED, HID, and halogen). |
| first_indexed | 2024-04-11T18:19:11Z |
| format | Article |
| id | doaj.art-c2cb4bf01cc34b76a5965e884448659f |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-11T18:19:11Z |
| publishDate | 2016-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-c2cb4bf01cc34b76a5965e884448659f2022-12-22T04:09:49ZengMDPI AGSensors1424-82202016-07-01167105810.3390/s16071058s16071058Hyperspectral Image-Based Night-Time Vehicle Light Detection Using Spectral Normalization and Distance Mapper for Intelligent Headlight ControlHeekang Kim0Soon Kwon1Sungho Kim2Department of Electronic Engineering, Yeungnam University, 280, Daehak-ro, Gyeongsan-si, Gyeongsangbuk-do KS011, KoreaDaegu Gyeongbuk Institute of Science and Technology, 333, Techno jungang-daero, Hyeonpung-myeon, Dalseong-gun, Daegu KS002, KoreaDepartment of Electronic Engineering, Yeungnam University, 280, Daehak-ro, Gyeongsan-si, Gyeongsangbuk-do KS011, KoreaThis paper proposes a vehicle light detection method using a hyperspectral camera instead of a Charge-Coupled Device (CCD) or Complementary metal-Oxide-Semiconductor (CMOS) camera for adaptive car headlamp control. To apply Intelligent Headlight Control (IHC), the vehicle headlights need to be detected. Headlights are comprised from a variety of lighting sources, such as Light Emitting Diodes (LEDs), High-intensity discharge (HID), and halogen lamps. In addition, rear lamps are made of LED and halogen lamp. This paper refers to the recent research in IHC. Some problems exist in the detection of headlights, such as erroneous detection of street lights or sign lights and the reflection plate of ego-car from CCD or CMOS images. To solve these problems, this study uses hyperspectral images because they have hundreds of bands and provide more information than a CCD or CMOS camera. Recent methods to detect headlights used the Spectral Angle Mapper (SAM), Spectral Correlation Mapper (SCM), and Euclidean Distance Mapper (EDM). The experimental results highlight the feasibility of the proposed method in three types of lights (LED, HID, and halogen).http://www.mdpi.com/1424-8220/16/7/1058intelligent transportation systemIntelligent Headlight Controlheadlight detectionhyperspectral imagerear lamp detectionspectral distance |
| spellingShingle | Heekang Kim Soon Kwon Sungho Kim Hyperspectral Image-Based Night-Time Vehicle Light Detection Using Spectral Normalization and Distance Mapper for Intelligent Headlight Control Sensors intelligent transportation system Intelligent Headlight Control headlight detection hyperspectral image rear lamp detection spectral distance |
| title | Hyperspectral Image-Based Night-Time Vehicle Light Detection Using Spectral Normalization and Distance Mapper for Intelligent Headlight Control |
| title_full | Hyperspectral Image-Based Night-Time Vehicle Light Detection Using Spectral Normalization and Distance Mapper for Intelligent Headlight Control |
| title_fullStr | Hyperspectral Image-Based Night-Time Vehicle Light Detection Using Spectral Normalization and Distance Mapper for Intelligent Headlight Control |
| title_full_unstemmed | Hyperspectral Image-Based Night-Time Vehicle Light Detection Using Spectral Normalization and Distance Mapper for Intelligent Headlight Control |
| title_short | Hyperspectral Image-Based Night-Time Vehicle Light Detection Using Spectral Normalization and Distance Mapper for Intelligent Headlight Control |
| title_sort | hyperspectral image based night time vehicle light detection using spectral normalization and distance mapper for intelligent headlight control |
| topic | intelligent transportation system Intelligent Headlight Control headlight detection hyperspectral image rear lamp detection spectral distance |
| url | http://www.mdpi.com/1424-8220/16/7/1058 |
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