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Method for retrieving vehicles on basis of sparse codes of features of vehicular ornaments

A sparse coding and decoration technology, applied in the field of intelligent transportation research

Inactive Publication Date: 2017-05-17
SOUTHEAST UNIV
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Problems solved by technology

[0003] The problem to be solved by the patent of the present invention is to effectively solve the vehicle image retrieval problem

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  • Method for retrieving vehicles on basis of sparse codes of features of vehicular ornaments
  • Method for retrieving vehicles on basis of sparse codes of features of vehicular ornaments

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Embodiment Construction

[0055] Below in conjunction with specific implementation mode, this technical solution is further described:

[0056] The first step: first train the feature library. Select only the vehicle positive sample pictures and only the background negative sample pictures for feature extraction of the gray level co-occurrence matrix, and perform training to obtain the detected feature library; quantify the gray level of the image, and the level of quantification in this patent is divided into 16 levels, Therefore, the dimension of its gray level co-occurrence matrix is ​​16×16 dimensions, which is selected in this patent Calculate the probability distribution of their relative positional offset by the diagonal relationship. Second, use the trained feature library for vehicle detection. First, grayscale the input image, and grid the image into M×N subimages of W×H size; then calculate the grayscale co-occurrence matrix features of each grid window image, and use the trained feature ...

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Abstract

The invention discloses a method for retrieving vehicles on the basis of sparse codes of features of vehicular ornaments. The method includes acquiring vehicle image data and detecting vehicle areas in images by the aid of gray co-occurrence matrix features and support vector machines; acquiring vehicular ornament area images in the vehicle images; creating over-complete dictionaries of the vehicular ornament area images; solving sparse vectors of the vehicular ornament area images corresponding to the to-be-inquired vehicles; reconstructing to-be-inquired vehicular ornament area images and computing Euclidean distances from reconstructed images to the to-be-inquired vehicular ornament area images; updating the sparse vectors of the to-be-inquired vehicular ornament area images, sorting elements of the sparse vectors according to the magnitude and setting thresholds to obtain retrieval results of the vehicular ornament area images. Compared with the prior art, the method has the advantages that the vehicles are retrieved on the basis of the features of the vehicular ornaments, accordingly, the retrieval precision and reliability can be greatly improved, and important bases can be provided for effectively solving problems in the aspect of illegal vehicle tracking.

Description

technical field [0001] The invention patent relates to the field of intelligent transportation research, especially the research on vehicle image retrieval methods. Background technique [0002] In order to solve the problems of urban development and realize the sustainable development of cities, the construction of "smart cities" has become an irreversible historical trend in the development of cities in my country today; at the same time, in order to meet the needs of urban security prevention and control and urban management, the Political and Legal Committee initiated The Ministry of Industry and Information Technology jointly built the "Skynet Project". The "Skynet Project" is to use image acquisition, transmission, control, display and other equipment and control software to monitor and record information in fixed areas in real time, and to provide technical support for extracting evidence of illegal and criminal activities of vehicles in the city. However, the main pr...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30G06K9/62
CPCG06F16/583G06F18/2136G06F18/28G06F18/2411
Inventor 赵池航林盛梅陈爱伟
Owner SOUTHEAST UNIV
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