Recognition of Bookmark Aging Degree Based on Probabilistic Neural Network. (16th February 2022)

• Record Type: Journal Article
• Authors: Zheng, Cong; Zhang, Xiaoling; Ma, Shaoqiu; Xiao, Zhijian
• Other Names: Kumar Akshi Academic Editor.
• Is Part Of: Computational intelligence and neuroscience. Volume 2022(2022)
• Publication Date: 2022-02-16
• Subjects: Neurosciences -- Data processing -- Periodicals; Computational intelligence -- Periodicals; Computational neuroscience -- Periodicals; 612.80285
• DOI: 10.1155/2022/3151441
• Languages: English
• ISSNs: 1687-5265

Abstract

Abstract : Bookmarks are the basis for librarians to get books on and off shelves and borrowers to borrow books. In order to solve the problem of time-consuming and labor-consuming manual checking of bookmark aging, this paper proposes a method of bookmark aging recognition based on image processing technology. First, we perform image preprocessing, Otsu threshold segmentation, and morphological processing on the acquired bookmark image to obtain the effective area of the bookmark, then acquire the aging features for the bookmark, and finally input the acquired features into the trained neural network for defect recognition. The experimental results show that the method proposed in this paper can achieve 96% recognition, which can more accurately identify the aging defects of bookmarks.