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Road Surface State Recognition Based on SVM Optimization and Image Segmentation Processing
2017
Journal of Advanced Transportation
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Next, a recognition method of road surface state based on SVM (Support Vector Machine) is proposed. ...
Adverse road condition is the main cause of traffic accidents. Road surface condition recognition based on video image has become a central issue. ...
[17] extracted RGB, HIS, and YUV of road surface images and established the road surface state recognition model based on improved BP neural network. ...
doi:10.1155/2017/6458495
fatcat:shydn4t4qjcv3nxykeeuuapamm
Enhancing road signs segmentation using photometric invariants
[article]
2020
arXiv
pre-print
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This method is based on color in-formation using a hybrid distance, by exploiting the chro-matic distance and the red and blue ratio, on l Theta Phi color space which is invariant to highlight, shading ...
In this paper, an efficient ap-proach of road signs segmentation based on photometric invariants is proposed. ...
Some works, try to tackle these problems by using optical image acquisition models based on color space representations [23] . ...
arXiv:2010.13844v1
fatcat:p5hdmrhcpzbqfj3rsmukxkrbbq
Research on Road Adhesion Condition Identification Based on an Improved ALexNet Model
2021
Journal of Advanced Transportation
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on an improved ALexNet model, namely, the road surface recognition model (RSRM), is proposed. ...
In this paper, considering that the process of manually extracting image features is complicated and that the extraction method is random for everyone, road surface condition identification method based ...
To solve these problems, this paper proposes a road surface condition identification method based on an improved ALexNet model, namely, the road surface recognition model (RSRM). erefore, the main contributions ...
doi:10.1155/2021/5531965
fatcat:hspqwn3rfbddngb2nnjioeqgee
Color machine vision for autonomous vehicles
1998
Engineering applications of artificial intelligence
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Color can be a useful feature in autonomous vehicle systems that are b ased on machine vision, for tasks such as obstacle detection, lane road following, and recognition of miscellaneous scene objects. ...
pixels based on the approximated function. ...
The reason color has not been used much in this domain is the lack of e ective color-based recognition methods for outdoor images. ...
doi:10.1016/s0952-1976(97)00079-1
fatcat:ho4ilx5dazb25lyxyfxmk43b2y
Design of a Multi-Sensor Cooperation Travel Environment Perception System for Autonomous Vehicle
2012
Sensors
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Multiple single scan lasers are integrated to detect the road curb based on Z-variance method. Vision based lane detection is realized by two scans method combining with image model. ...
Haar-like feature based method is applied for traffic sign detection and SURF matching method is used for sign classification. ...
When the road condition is complex, these methods may easily fail. Common road models include triangle model, straight line model, clothoid model, polynomial model and spline model, etc. Wang et al. ...
doi:10.3390/s120912386
fatcat:jhe6g7t3nnapzfqow3k6yhhl5u
Design 3D Visualization Digital Road System of Pavement Distress
2017
DEStech Transactions on Engineering and Technology Research
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This research design 3D visualization digital road system of pavement distress, Road disease integrity detection based on three-dimensional visualization reconstruction have been realized, compared with ...
The traditional detection methods at present cannot meet the real needs of the road maintenance organization. ...
The principle of making colored road is based on the terrain, making the corresponding color table. ...
doi:10.12783/dtetr/mdm2016/4979
fatcat:bukdrr6orvaipdoudvv5cykuby
Computer Vision Systems for "Context-Aware" Active Vehicle Safety and Driver Assistance
[chapter]
2011
Digital Signal Processing for In-Vehicle Systems and Safety
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Road Sign Recognition Algorithm The methods used for automatic road sign recognition can be classified into three groups: color based, shape based and others. ...
Model based approaches are found to be more robust compared to feature-based methods, for example in [6] B-snake is used to represent the road. ...
doi:10.1007/978-1-4419-9607-7_15
fatcat:ew343vav2ndb5mi2idbu2itnxa
Gradation Image Processing for Text Recognition in Road Signs Using Image Division and Merging
2014
The Journal of The Korea Institute of Intelligent Transport Systems
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Multi-threshold values of natural scene images are used to improve the extraction rate of texts and figures based on pattern recognition. ...
This paper proposes a gradation image processing method for the development of a Road Sign Recognition Platform (RReP), which aims to facilitate the rapid and accurate management and surveying of approximately ...
Most color-based traffic sign extraction methods detect areas similar to a traffic sign using an image segmentation method based on the RGB, HIS and HSV color model [2] [3] [4] . ...
doi:10.12815/kits.2014.13.2.027
fatcat:7irop3inbvem7gfkajs6ghgo3y
Non-parametic model for robust road recognition
2010
IEEE 10th INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING PROCEEDINGS
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The model keeps a set of sample for both road region and off-road region, and then estimates the probability of a newly pixel based on color information. ...
Road recognition is one of the key technologies in the vision-based intelligent navigation system. ...
ACKNOWLEDGMENT Beyond the financial support, the authors are also grateful to the opened road image test set provided by the Robotics Institute at Carnegie Mellon University. ...
doi:10.1109/icosp.2010.5655958
fatcat:dluymudacffslmw4edmqe4fwcy
Traffic Light Detection and Recognition for Self Driving Cars using Deep Learning Survey
2020
Zenodo
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By using deep learning, a deep neural network based model is proposed for reliable detection and recognition of traffic lights TL . ...
Aswathy Madhu | Sruthy S "Traffic Light Detection and Recognition for Self Driving Cars using Deep Learning: Survey" Published in International Journal of Trend in Scientific Research and Development ( ...
The non-ground points are firstly segmented from raw MLS data by estimating road ranges based on vehicle trajectory and geometric features of roads (e.g., surface normal and planarity). ...
doi:10.5281/zenodo.3842837
fatcat:ysm3lpbtyjgtnfsorvscf7eycu
Investigating the Daytime Visibility Requirements of Pavement Marking Considering the Influence of CCT and Illuminance of Natural Light
2022
International Journal of Environmental Research and Public Health
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The luminance contrast of the pavement marking to the surrounding road surface ranged from 0 to 10. ...
Based on analyzing the mechanism and impact factors of daytime visibility of pavement markings, a subjective scale of pavement markings state in the drivers' field of view was proposed and a short and ...
This study obtained the daytime visibility requirements of pavement marking considering the most unfavorable conditions. ...
doi:10.3390/ijerph19053051
pmid:35270742
pmcid:PMC8910019
fatcat:gvmwdsdzxzhajm3kozgqge5nzq
Rural Road Detection of Color Image in Complicated Environment
2013
International Journal of Signal Processing, Image Processing and Pattern Recognition
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For color image having more information, we detect road area based on color image [13] . The key of color image segmentation is the chosen of image space. ...
To realize rural road detection in complication environment, a method based on improved FCM (Fuzzy C-Means) and Hough transformation has been proposed. ...
The method of based on road model contains three steps: assuming road has regular boundary; establishing lots of road model; finding appropriate road model based on image. ...
doi:10.14257/ijsip.2013.6.6.15
fatcat:gu47lzferrdxhm25erj5jfispu
Asphalt-surface defects detection, based on Tyre/Road noise analysis and geo-processing
2019
Proceedings of the ICA congress
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A new approach to detect different asphalt defectology based on tyre/road noise analysis by Machine Learning algorithms is proposed. ...
In this probe of concept, a group of four local and distributed road-surface defects were automatically detected and plotted on map. ...
The conformed data let us to implement a machine learning model based on Nearest Neighbors classifier with an average accuracy gre ater than 92%. ...
doi:10.18154/rwth-conv-238915
fatcat:f5t25me3hzgxpoanzome7dabha
Smartphone-based Estimation of Sidewalk Surface Type via Deep Learning
2021
Sensors and materials
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We, therefore, propose a method of estimating the sidewalk surface type by applying a convolutional neural network (CNN) based on the VGG16 architecture to sensor data. ...
During training, the model was pretrained with the human activity sensing consortium (HASC) dataset, a large benchmark for human activity recognition, as a source domain, and we applied fine-tuning (FT ...
Nomura and Shiraishi (14) proposed a method of estimating road surface conditions from acceleration data from a smartphone placed on the dashboard of a car. ...
doi:10.18494/sam.2021.2976
fatcat:ea7b4zjjdjatviohpatfm6sh24
AUTOMATIC TRAFFIC SIGN DETECTION AND RECOGNITION USING MOBILE LIDAR DATA WITH DIGITAL IMAGES
2020
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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The traffic sign detection and recognition method includes two steps: traffic sign interest regions are first extracted from mobile LiDRA data. ...
This paper presents a traffic sign detection and recognition method from mobile LiDAR data and digital images for intelligent transportation-related applications. ...
Normalized digital surface model (nDSM), a representation of elevated objects on a flat surface, is generated by subtracting digital terrain model (DTM) from digital surface model (DSM). ...
doi:10.5194/isprs-archives-xliii-b3-2020-599-2020
fatcat:wilpzor7yzclnhprt2nrz6qmzu
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