Dimensional Defect Detection Research on the Sculpture Surface Combining the Convolutional Neural Network and Gabor

Abstract

Thematic sculpture creation is an important part of sculpture creation. In particular, the current thematic sculpture creation in China has broken the shackles of serving politics and has shown a variety of aspects such as theme selection, modelling method, material language, and creative purpose. Since the new century, Chinese thematic sculptors have made in-depth analysis and research on the diversity of creative objects, the infinite possibilities of creative expression, and the diversity of creative purposes, especially through the phenomenon of different thematic sculptures to explore their existing predicaments, and give them reflection. If the time is too long, it will reduce the production efficiency of the sculpture production line and increase the operating cost of the enterprise. The Gabor wavelet transform is used to obtain the texture features of the sculpture surface, and the generated high-dimensional features are subjected to random projection dimension reduction. Finally, the binarization algorithm can be used to detect the defect location quickly and accurately. The feature map is extracted by selecting a deep network. The neural network algorithm structure for the sculpture dataset is presented, and the activation function and regularization method are improved on this basis.