Vehicles Categorization in Complex Background

Abstract:

This paper presents a novel approach to categorize multi-view vehicles in complex background using only two dimension characteristic vectors instead of high dimension vectors. Vehicles have large variability of models and the view-point makes the appearance change dramatically. Significant characteristics should be chosen as the evidence to categorize. In this paper, we categorize the vehicles into two categories – cars and lorries. Line detection method is used and calculating the average line length and the number of parallel lines as the two characteristics. A linear classifier is trained using 30 different view cars and lorries as the training set and an 10 additional different cars and lorries as the testing set.

• Periodical: Advanced Materials Research (Volumes 998-999)
• Pages: 708-711
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.998-999.708
• Online since: July 2014
• Authors: Ying Zhuo Xiang*, Dong Mei Yang, Ji Kun Yan
• Keywords: Digital Image Processing, Feature Extraction Method, Object Categorization, Vehicle Categorization

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