Research on Image Database Classification Method Based on MHPA

Due to the image database size expanding, how to effectively classify and retrieve images has become an important research topic. This paper proposes an image database classification method based on a multi-step heuristic partitioning algorithm (MHPA) and convolutional neural network, aiming to improve the accuracy and efficiency of image classification, provide an overview of the principle and process of the MHPA and the methods and techniques for extracting features from images. Furthermore, this paper designs a system based on an MHPA and convolutional neural network, including image acquisition, preprocessing, and image classification modules. This paper describes the structure and parameters of the convolutional neural network model and the model training and optimization process. Finally, this paper verifies the effectiveness and superiority of this method through experiments, analyzes the experimental results, and gives conclusions and prospects.