Research on Random Forest-based Pattern Recognition Method for Conservation of Cultural Heritage of Mural Paintings in Tomb Chambers

Abstract

The development of digital technology has made the use of machine learning algorithms to protect cultural heritage has become a trend. In this paper, based on the random forest algorithm, the conservation model of tomb mural cultural heritage is recognized. The mural paintings in the tomb of Prince Zhanghuai are used as the data source to construct the tomb mural painting dataset, and the images in the dataset are processed, augmented and labeled. The features such as color, texture and shape in the mural images are extracted as one of the input information of the cultural heritage protection model of the tomb murals. Based on the random forest algorithm, a pattern recognition model for the protection of cultural heritage of tomb frescoes is constructed, and the feature vectors obtained from the feature extraction are used to calculate the split points of the decision tree. The classification results of multiple decision trees are weighted and averaged to obtain the final recognition results. The recognition accuracies of this paper’s model on the training set, test set and validation set are 99.45%, 95.46% and 92.58%, respectively. This is a significant improvement over other existing algorithms. Meanwhile, the algorithm consumes significantly less time than the ResNet18 deep residual network model before and after data enhancement, and is able to efficiently accomplish the task of recognizing the protection of cultural heritage of tomb chamber murals.