Digital Image Processing Using MATLAB
Digital Image Processing Using MATLAB
Short Communication: Digital image restoration by Wiener filter in 2D case
Advances in Engineering Software
Unsupervised pattern recognition models for mixed feature-type symbolic data
Pattern Recognition Letters
Improving nearest neighbor rule with a simple adaptive distance measure
ICNC'06 Proceedings of the Second international conference on Advances in Natural Computation - Volume Part I
Learning, Modeling, and Classification of Vehicle Track Patterns from Live Video
IEEE Transactions on Intelligent Transportation Systems
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Automatic vehicle classification is an important task in Intelligent Transport System (ITS) because it allows the traffic parameter, called vehicles count by category, to be obtained. In terrestrial public roads, variants sources of information for vehicles counter by category have been used such as video, magnetic induction coil, sound sensors, temperature sensors and microwave. The use of video has increased support for traffic management due to the advantages of installation cost and a wide range of information it contains. This paper presents comparison of vehicle image classification based on edge features. Contour points number, height, width and fractal dimension are used like features. Nearest neighbor, adaptive nearest neighbor and adaptive distance are used in classification. The experimental platform is built on Matlab R2009a.