Cars logo recognition by using of backpropagation neural networks

Abstract

Numerous developments in creating “intelligent” programs have been made, some of which have drawn inspiration from biological neural networks. Researchers are developing artificial neural networks (ANNs) from various scientific fields to address multiple issues in prediction, control, and optimization. Many s, densely connected processors make up artificial neural networks, which can be considered parallel and distributed processing systems. This paper uses a back propagation ANN algorithm to recognize cars' logos. Sixty-eight images are used, which represents the logo of vehicles and their distortion and rotation, to simulate human eye recognition. The proposed design is trained by using a supervised learning algorithm. The designed system successfully validates the car logos by 99.6%, which consider a high percentage in such a field. Finally, the implemented system presents a real-life application of ANN.