Color recognition of design object of manual decoration element based on convolution neural network under the impact of COVID-19

Abstract

The popularity of covid-19 has led to the introduction of the policy of controlling the flow of personnel, which has a certain impact on the color recognition of the design objects of hand decorative elements. In the past, the research on convolution neural network design and color recognition is still in the traditional method, and the field of computer vision is not really combined with the traditional decorative fabric. This paper proposes a solution based on deep learning. Color learning and main color recognition can be processed as a whole. By introducing convolution neural network, the scheme can learn color features directly from the image itself, and the process of artificial design features is omitted. While simplifying the process of model building and training, the potential information association can be obtained, so as to obtain better recognition effect. In addition, due to the deep depth of the network, this paper uses the initial optimization module to avoid the performance degradation and over fitting in the training process. This method has an important reference value for the color design of modern hand decoration, and can promote the development of hand decoration during the popularity of covid-19.