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Vehicle logo automatic identification method based on principal component analysis convolutional neural network

A technology of convolutional neural network and principal component analysis, applied in biological neural network models, neural architecture, character and pattern recognition, etc., can solve problems such as recognition rate and recognition speed need to be improved

Active Publication Date: 2016-04-20
JIANGSU AEROSPACE DAWEI TECH CO LTD
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AI Technical Summary

Problems solved by technology

At present, the existing technologies of vehicle identification include the classification method using feature invariant moment distance, the recognition method based on SIFT features, etc., which need to be improved in recognition rate and recognition speed

Method used

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  • Vehicle logo automatic identification method based on principal component analysis convolutional neural network
  • Vehicle logo automatic identification method based on principal component analysis convolutional neural network
  • Vehicle logo automatic identification method based on principal component analysis convolutional neural network

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Embodiment Construction

[0043] A method for automatic recognition of car logos based on principal component analysis convolutional neural network, including ideal output feature vector T for classification of various car logos k Obtaining steps and vehicle logo recognition steps, wherein, T k Indicates the ideal output feature vector of car logo classification, k represents the number of car logo types,

[0044] The ideal output feature vector T of the classification of various vehicle logos k The steps taken include:

[0045] Collect N copies of various car logo images as sample images. In this embodiment, N can be 5000 or 6000, and the various car logo images are respectively positioned to obtain various car logos with a size of 44×44 pixels N parts of the grayscale image are accurately positioned in the region, and then through training the convolutional neural network, determine and obtain the ideal output feature vector T of various vehicle logo classifications. The training method of the conv...

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Abstract

The invention provides a vehicle logo automatic identification method based on a principal component analysis convolutional neural network. The method comprises a step of obtaining various vehicle logo classification ideal output feature vectors Tk, and a step of vehicle logo identification, wherein the Tk represents the vehicle logo classification ideal output feature vectors, k represents a vehicle logo classification number, the various vehicle logo classification ideal output feature vectors Tk are obtained from training the convolutional neural network by using N various types of vehicle logo image samples, and according to the vehicle logo identification, after the output vector Z of a vehicle logo to be identified is obtained, through calculating the Euclidean distance and the degree of membership between the vehicle logo classification ideal output feature vectors Tk of various brands and corresponding output vector Z of the vehicle logo to be identified, the corresponding brand vehicle logo in a largest degree of membership is the vehicle logo to be identified.

Description

technical field [0001] The technical field of vehicle feature detection in traffic images, in particular, relates to an automatic identification method for vehicle logos based on principal component analysis convolutional neural network. Background technique [0002] As an important part of the technical field of vehicle feature detection in traffic images, vehicle logo recognition can obtain vehicle information more accurately, and has been more and more widely used in the automatic recording of vehicle whereabouts and illegal vehicles. At present, the existing technologies for vehicle logo recognition include the classification method using feature invariant moment distance, SIFT-based feature recognition method, etc., which need to be improved in recognition rate and recognition speed. [0003] Convolutional neural network (CNN) is a kind of artificial neural network, which is mainly used to recognize two-dimensional graphics with displacement, scaling and other forms of ...

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Application Information

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IPC IPC(8): G06K9/62G06K9/32G06N3/04
CPCG06V10/25G06V2201/08G06N3/045G06F18/24
Inventor 狄明珠韩晶方亚隽
Owner JIANGSU AEROSPACE DAWEI TECH CO LTD
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