Truck re-identification method based on deep neural network and feature fusion

• Main Authors: YAN RUGEN, ZHOU PING, LYU QIANG, CHEN CHEN, ZHAO JIXIANG, HU CHANGLONG, LI TAO
• Format: Patent
• Language: Chinese; English
• Published: 13.01.2023
• Subjects: CALCULATING; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS; COMPUTING; COUNTING; ELECTRIC DIGITAL DATA PROCESSING; PHYSICS

The invention discloses a truck re-identification method based on a deep neural network and feature fusion, and the method comprises the steps: obtaining a truck image, dividing the truck image, and carrying out the preprocessing and standardization of the space and size of the image; based on a deep convolutional neural network and the preprocessed picture, constructing a deep convolutional neural network model and training the deep convolutional neural network model and a set loss function; testing according to the trained deep convolutional neural network model; and finally, carrying out truck re-identification retrieval by utilizing the similarity matrix to obtain a most similar truck picture. Truck photo features are obtained based on the deep neural network and feature fusion, and then overall feature representation is obtained through feature fusion. Therefore, the problems of license plate counterfeiting, removal, shielding and the like caused by difficulty in retrieval due to small truck difference i