Abstract
This study suggests a method to detect multiple vehicles, which is important for driving assistance system. In a frame of color image, shadow information and edge elements are used to detect vehicle candidate areas. Detecting the areas of multiple vehicles requires to analyze Estimation of Vehicle (EOV) and Accumulated Similarity Function (ASF) from the vehicle candidate areas that exist in image sequences. Later by evaluating the possibility of vehicles, it determines the vehicle areas. Most studies focus on detecting a single vehicle in front. This study, however, focuses on detecting multiple vehicles even in heavy traffic and frequent change of lanes.
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Han, S., Ahn, E., Kwak, N. (2005). Detection of Multiple Vehicles in Image Sequences for Driving Assistance System. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2005. ICCSA 2005. Lecture Notes in Computer Science, vol 3480. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11424758_117
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DOI: https://doi.org/10.1007/11424758_117
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25860-5
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