Abstract
Counting and organization of books in libraries is a routine and time-consuming task. The task gets more complicated by misplaced books in shelves. In order to solve these problems, we propose an automated visual call number (book-id) detection and counting system in this paper. The method employs a Haar feature-based classifier from OpenCV library and cloud-based OCR system to decode characters from images. To develop and test the method, we have acquired and organized a dataset of 1000 book call numbers. The proposed method has been tested on 20 bookshelves images that contain 233 call numbers, which resulted in a true detection rate of 96% and false detection rate of 1.75 per image. For OCR step, the number of false recognized characters per call number was 0.76.
Original language | English |
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Title of host publication | UBMK 2018 - 3rd International Conference on Computer Science and Engineering |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 504-508 |
Number of pages | 5 |
ISBN (Electronic) | 9781538678930 |
DOIs | |
Publication status | Published - 6 Dec 2018 |
Externally published | Yes |
Event | 3rd International Conference on Computer Science and Engineering, UBMK 2018 - Sarajevo, Bosnia and Herzegovina Duration: 20 Sept 2018 → 23 Sept 2018 |
Publication series
Name | UBMK 2018 - 3rd International Conference on Computer Science and Engineering |
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Conference
Conference | 3rd International Conference on Computer Science and Engineering, UBMK 2018 |
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Country/Territory | Bosnia and Herzegovina |
City | Sarajevo |
Period | 20/09/18 → 23/09/18 |
Bibliographical note
Publisher Copyright:© 2018 IEEE.
Keywords
- Call Number Detection
- HAAR Classifier
- Library Automation
- OCR