Dr. Nattachai Watcharapinchai Profile

Dr. Nattachai Watcharapinchai

Sr Assistant Researcher at National Electronics and Computer Technology Ctr

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SPIE Journal Paper | 25 July 2017

Automatic vehicle classification using linked visual words

Nattachai Watcharapinchai, Supavadee Aramvith, Supakorn Siddhichai

JEI, Vol. 26, Issue 04, 043009, (July 2017) https://doi.org/10.1117/12.10.1117/1.JEI.26.4.043009

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An improvement in the method of automatic vehicle classification is investigated. The challenges are to correctly classify vehicles regardless of changes in illumination, differences in points of view of the camera, and variations in the types of vehicles. Our proposed appearance-based feature extraction algorithm is called linked visual words (LVWs) and is based on the existing technique bag-of-visual word (BoVW) with the addition of spatial information to improve accuracy of classification. In addition, to prevent over-fitting due to a large number of LVWs, four common sampling techniques with LVWs are investigated. Our results suggest that the sampling of LVWs using TF-IDF with grouping improved the accuracy of classification for the test dataset. In summary, the proposed system is able to classify nine types of vehicles and work with surveillance cameras in real-world scenarios. The classification accuracy of the proposed system is 5.58% and 4.27% higher on average for three datasets when compared with BoVW + SVM and Lenet-5, respectively.

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