In order to improve the intelligence of digital library image resources, this paper proposes an efficient retrieval technology of digital library image resources based on deep learning and semantic feature extraction, which uses infrared and radio frequency transverse scanning technology to scan the front cover and back cover of digital library image resources, and divides the text and image regions of scanned digital library image resources infrared and radio frequency images. In the infrared and radio frequency transmission space, the collected scanned image resources of digital library are subjected to semantic diversification feature decomposition and feature separation, and the binary semantic ontology information features of digital library image resources are extracted. Combined with the image semantic feature extraction method, the convergence control in the process of extracting the structural features of digital library image resources is realized, and the digital library image resources are retrieved based on the extracted library resource information feature components. Simulation results show that this method has higher precision and shorter retrieval time, which improves the retrieval efficiency of digital library.