Vehicle classification method based on multi-feature fusion
A multi-feature fusion and vehicle classification technology, which is applied in the field of vehicle classification based on multi-feature fusion, can solve the problems of insufficient theoretical basis, many empirical components, and complex calculations, so as to alleviate the problems of too much experience and theoretical basis. Sufficient and effective fusion effect
Active Publication Date: 2017-10-31
TONGJI UNIV
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Problems solved by technology
The template matching method has the disadvantages of complex calculation and relatively poor real-time performance.
In the pattern recognition method, feature extraction includes geometric features such as vehicle length, vehicle width, and vehicle height, texture features such as invariant moments, gray-level co-occurrence matrix, and edge features such as HOG, SIFT, and EOH. The selection process of these features is It is artificially designed, with a lot of empirical elements, and the theoretical basis is not very sufficient
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[0037] The technical solution of the present invention will be further described below in conjunction with the accompanying drawings.
[0038] Principle: The present invention proposes a method based on multi-feature fusion to effectively identify and classify vehicle models in real-time video. Add the high-order feature descriptors of the underlying pixels of the vehicle image mined through the deep belief network to the traditional artificially designed features, and use the support vector machine to train the fusion features to build a vehicle classifier.
[0039] The vehicle model classification method based on multi-feature fusion in the present invention, the extracted vehicle model features are based on the artificially designed features by adding high-order features excavated from the underlying pixels of the vehicle picture, and the globality of the artificially designed features is preserved through feature fusion , and deeply dig out the underlying features of the v...
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The invention relates to a vehicle classification method based on multi-feature fusion. The steps are: (1) detect, locate and segment the vehicle in the video; (2) perform morphological processing on the segmented vehicle image, and extract three features of the vehicle image for effective fusion; (3) use The support vector machine trains the fusion features to form a vehicle classifier, which can effectively classify the vehicles in the real-time video. Compared with the prior art, the present invention can reduce the empirical component of the extracted features, so that the theoretical basis of feature extraction is more sufficient, thereby improving the effect of vehicle classification.
Description
technical field [0001] The invention relates to a vehicle classification method, in particular to a vehicle classification method based on multi-feature fusion. Background technique [0002] With the development of my country's social economy, the number of automobiles has increased rapidly, and the types of automobiles are also intricate. Traffic scheduling and toll collection have become common problems in daily life. With the development of intelligent transportation systems, with the help of gradually mature video analysis technology, the accurate identification and classification of vehicle models in traffic videos has become the application of various toll monitoring systems, large parking lot monitoring systems, and traffic monitoring and command systems. and development basis. [0003] At present, video-based vehicle identification and classification are mainly based on template matching and pattern recognition methods. The template matching method first establishes...
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IPC IPC(8): G06K9/66G06K9/46
CPCG06V10/50G06F18/2411
Inventor 蒋昌俊陈闳中闫春钢张亚英刘春梅钱华
Owner TONGJI UNIV