从多单元书架图像中识别图书标题的方法

Nuzhat Tabassum, Sujan Chowdhury, M. Hossen, Salah Uddin Mondal
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引用次数: 6

摘要

从书架图像中进行图书检测和标题识别的传统方法有很多。但这些方法大多是在单行书架图像上工作的。本文提出了一种从多行书架图像中分割书脊并识别书名的技术。从图像中检测和提取水平边缘以指示单个行。这些分隔行图像将在下一个模块中使用,其中提取垂直线以分割图书区域。随后,所有书脊图像都被转换成二值图像。在下一步,使用区域属性删除小的和不需要的对象,然后从单个书脊中提取标题。然后利用边界框和连通分量区域对标题字符进行分割和提取。通过应用模板匹配,将分隔字符图像与数据集图像进行匹配或不匹配。因此,开发的新方法可以识别标题。系统的整体设计起到了一定的作用,但从多单元图像中提取图书标题是本文的主要内容。为了测试所提出的框架,使用了不同条件下的书架图像,并给出了结果来证明该框架的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An approach to recognize book title from multi-cell bookshelf images
There are many conventional methods for book detection and title recognition from bookshelf images. But most of these methods are worked on single row bookshelf images. Here this paper presents a technique for segmenting books spine and recognizing book title from multi-row bookshelf images. Horizontal edges are detected and extracted from the images as to indicate individual rows. These separated row images are used in the next module where vertical lines are extracted in order to segment the book regions. Later all book spine images are converted into binary images. At the next step, small and unwanted objects are removed using region properties and subsequently and extracts titles from individual book spines. Then the characters of the title are segmented and extracted by using bounding box and connected component region. Separated character images are matched or unmatched with the data set images by applying template matching. As a result, the developed new method recognizes the title. The system design as a whole makes a contribution, but the extraction of the book titles from the multi-cell images makes the main principal of this paper. To test the proposed framework various bookshelf images with a variety of conditions are used and results are presented to prove its effectiveness.
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