A Haar Classifier B ased C all N umber Detection and Counting Method for Library Books

Kanburoglu A. B., Tek F. B.

3rd International Conference on Computer Science and Engineering (UBMK), Sarajevo, Bosnia And Herzegovina, 20 - 23 September 2018, pp.504-508 identifier

  • Publication Type: Conference Paper / Full Text
  • City: Sarajevo
  • Country: Bosnia And Herzegovina
  • Page Numbers: pp.504-508
  • Keywords: Library Automation, Call Number Detection, HAAR Classifier, OCR
  • Istanbul Technical University Affiliated: No

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.