A Car Brand Recognition Method Based on Feature Grouping Bilinear Convolutional Neural Network

Abstract

The invention relates to the technical field of fine-grained classification of images, in particular to a method for car brand recognition based on a feature grouping bilinear convolutional neural network. Identify and crop out the area containing the vehicle in the original image; Step 2: Perform data expansion on the cropped image obtained in Step 1, so that the data set meets the training requirements of the bilinear convolution model for feature grouping; Step 3: Use the expanded image The data set trains the bilinear convolution model based on feature grouping; Step 4: The bilinear convolution network based on feature grouping performs car brand recognition on the input image; it solves the problem that the traditional vehicle recognition method is easily disturbed by complex background and recognizes The problem of too many model parameters is difficult to deploy; the target detection model is used in combination to extract the target area, which eliminates most of the background information and reduces the recognition difficulty of the model.

Description

technical field [0001] The invention relates to the technical field of fine-grained classification of images, and is used to solve the problems that traditional vehicle identification methods are easily interfered by complex backgrounds and the identification model parameters are too large and difficult to deploy, and in particular relates to a bilinear convolutional neural network based on feature grouping. Methods of car brand recognition. Background technique [0002] The car brand recognition technology is mainly through a series of processing work on the input image, and then finds out the specific area where the car is located in the image, and then performs brand recognition on the car. In today's daily production and life, car brand recognition technology is used in urban smart There are huge application prospects in the fields of transportation and Internet image retrieval. [0003] The original bilinear convolutional neural network adopts a bilinear mechanism and ...

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Problems solved by technology

[0005] The purpose of the present invention is to: solve the problem that the traditional vehicle recognition method is easily disturbed by complex backgrounds and too many recognition model parameters are not easy to deploy, and provide a car brand recognition method based on feature grouping bilinear convolutional neural network. The target detection model is used to extract the target area, most of the background information is eliminated, and the recognition difficulty of the model is reduced; the original bilinear convolutional neural network is improved, and the target detection model SSD is first used to process the image first. Target extraction; secondly, the bilinear model structure is also improved, and the feature grouping module is used to greatly reduce the overall parameter amount of the model, making it easier to deploy the model in actual scenarios; to realize the recognition of vehicles in complex backgrounds

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