TY - JOUR
T1 - Low-resolution vehicle image recognition technology by frame-composition of moving images
AU - Kanzawa, Yusuke
AU - Kobayashi, Hiroki
AU - Ohkawa, Takenao
AU - Ito, Toshio
PY - 2008
Y1 - 2008
N2 - Developing on-board automotive driver assistance systems aiming to alert drivers about driving environments, and possible collision with other vehicles has attracted a lot of attention lately. Especially, many researchers have suggested the forward vehicle recognition technology by a camera on vehicle. In the forward vehicle recognition, however, it is difficult to detect the features of vehicle from a distant vehicle image by conventional methods because the image is too low-resolution (LR). This paper presents vehicle image recognition technology for detecting of the features of a distant vehicle by frame-composition of moving images. To detect the vehicle features of a distant LR vehicle image, we use the moving images obtained from the camera on the vehicle, and utilize super-resolution (SR) image reconstruction. SR image reconstruction is to use signal processing techniques to obtain a high-resolution (or sequence) image from observed multiple LR images. Use of this technique on real road image, we show the effectiveness of the proposed techniques.
AB - Developing on-board automotive driver assistance systems aiming to alert drivers about driving environments, and possible collision with other vehicles has attracted a lot of attention lately. Especially, many researchers have suggested the forward vehicle recognition technology by a camera on vehicle. In the forward vehicle recognition, however, it is difficult to detect the features of vehicle from a distant vehicle image by conventional methods because the image is too low-resolution (LR). This paper presents vehicle image recognition technology for detecting of the features of a distant vehicle by frame-composition of moving images. To detect the vehicle features of a distant LR vehicle image, we use the moving images obtained from the camera on the vehicle, and utilize super-resolution (SR) image reconstruction. SR image reconstruction is to use signal processing techniques to obtain a high-resolution (or sequence) image from observed multiple LR images. Use of this technique on real road image, we show the effectiveness of the proposed techniques.
KW - Computer vision
KW - Frame-composition
KW - Super-resolution
KW - Vehicle recognition
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U2 - 10.1541/ieejeiss.128.1096
DO - 10.1541/ieejeiss.128.1096
M3 - Article
AN - SCOPUS:72349097878
VL - 128
SP - 12+1096-1101
JO - IEEJ Transactions on Electronics, Information and Systems
JF - IEEJ Transactions on Electronics, Information and Systems
SN - 0385-4221
IS - 7
ER -