A Haar Classifier Based Call Number Detection and Counting Method for Library Books Kütüphane Kitaplarinda Yer Numaralarini Bulmakve Saymakiç in HaarSiniflandirici Tabanlibir Yöntem

Ali Bugra Kanburoglu, F. Boray Tek

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

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 languageEnglish
Title of host publicationUBMK 2018 - 3rd International Conference on Computer Science and Engineering
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages504-508
Number of pages5
ISBN (Electronic)9781538678930
DOIs
Publication statusPublished - 6 Dec 2018
Externally publishedYes
Event3rd International Conference on Computer Science and Engineering, UBMK 2018 - Sarajevo, Bosnia and Herzegovina
Duration: 20 Sept 201823 Sept 2018

Publication series

NameUBMK 2018 - 3rd International Conference on Computer Science and Engineering

Conference

Conference3rd International Conference on Computer Science and Engineering, UBMK 2018
Country/TerritoryBosnia and Herzegovina
CitySarajevo
Period20/09/1823/09/18

Bibliographical note

Publisher Copyright:
© 2018 IEEE.

Keywords

  • Call Number Detection
  • HAAR Classifier
  • Library Automation
  • OCR

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