Human and vehicle infrared thermal image recognition method based on convolutional neural network

Abstract

The invention discloses a human and vehicle infrared thermal image recognition method based on a convolutional neural network. After the training set is augmented, the established infrared thermal image human and vehicle identification network model W-DenseNet is trained; a test set is used for verification to obtain an infrared thermal image human and vehicle identification network model W-DenseNet with high identification degree; the infrared thermal image human and vehicle identification network model W-DenseNet extracts features of different levels of data layer by layer, so that a machineobtains higher level of feature expression and understanding ability, the target category is effectively distinguished, and the purpose of identifying people and vehicles is achieved. A weight parameter learning module is added, so that weight parameters learned in network structure training are weighted on the corresponding convolution layer input feature map, important features are enhanced, invalid features are suppressed, and more effective features are extracted, and therefore, the accuracy of the network model for identifying the gender of men and women in the infrared thermal image canbe improved.

Description

technical field [0001] The invention belongs to the technical field of image recognition, and in particular relates to a method for recognizing infrared thermal images of people and vehicles based on a convolutional neural network. Background technique [0002] The imaging of cameras based on thermal infrared rays is not affected by the light source, especially in low-light conditions such as night and foggy days, and it can still image effectively. Infrared thermal imaging cameras have been widely used in tasks such as intelligent monitoring, disaster search and rescue, and intelligent assisted driving of automobiles. The most common targets in these tasks are people and vehicles, and machine recognition technology for infrared thermal images of people and vehicles plays an important role. Its high accuracy and all-weather characteristics can quickly and accurately identify and record the gender of vehicles and people, assist users to take corresponding actions or measures,...

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Problems solved by technology

[0008] Aiming at the above-mentioned deficiencies in the prior art, the present invention provides a human and vehicle infrared thermal image recognition method based on a convolutional neural network, which solves the problems of existing image recognition methods based on a convolutional neural network that contain non-living objects and have complex backgrounds. The problem of poor recognition effect of infrared thermal image

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