Research Article
CNN-Based Book Cover and Back Cover Recognition and Classification
@INPROCEEDINGS{10.1007/978-3-030-77428-8_5, author={Haochang Xia and Yali Qi and Qingtao Zeng and Yeli Li and Fucheng You}, title={CNN-Based Book Cover and Back Cover Recognition and Classification}, proceedings={Tools for Design, Implementation and Verification of Emerging Information Technologies. 15th EAI International Conference, TridentCom 2020, Virtual Event, November 13, 2020, Proceedings}, proceedings_a={TRIDENTCOM}, year={2021}, month={5}, keywords={CNN Deep learning Image recognition Image classification}, doi={10.1007/978-3-030-77428-8_5} }- Haochang Xia
Yali Qi
Qingtao Zeng
Yeli Li
Fucheng You
Year: 2021
CNN-Based Book Cover and Back Cover Recognition and Classification
TRIDENTCOM
Springer
DOI: 10.1007/978-3-030-77428-8_5
Abstract
As an important part of the national economy and an important supporting industry, printing and publishing industry is closely related to the development of national economy. In recent years, the massive publication and printing of books has made the work of storing books in databases more and more onerous. The maturity of deep learning technology has brought good news to recognition and classification of books. Convolutional neural network is a good tool. Convolutional neural network is a technology in deep learning, often used in computer vision, image recognition classification and other fields. Research results in the field of book recognition and classification are relatively lacking. There is no good book data set that can be used for neural network training. In this paper, we collected a large number of book data sets and we built a set of image classification models based on CNN to identify and classify the cover and back cover of books. Through a lot of training and testing, we have generated a set of CNN models that can effectively identify and classify the cover and back cover of books. Compared with the traditional way of manually entering books into database, the use of neural networks makes the work more efficient and saves a lot of human resources.
