Title: Application of optical character recognition with Tesseract in logistics management

Authors: Sigurd A. Berg; Soo-Yeon Seo; Richard H.Y. So

Addresses: Department of Industrial Engineering and Logistics Management, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong ' Department of Industrial Engineering and Logistics Management, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong ' Department of Industrial Engineering and Logistics Management, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong

Abstract: Warehouse and inventory management poses many challenges, for example in carton handling when upstream suppliers use labelling systems that are incompatible with a company's downstream system. In such cases, information is digitised using manual labour: this process can often become a bottleneck and, eventually, a source of handling errors. In this paper, the feasibility of applying optical character recognition (OCR) technology in carton handling is assessed, and a prototype based on the open-source engine Tesseract is described in detail. Its performance on both printed and handwritten text is quantified, as well as the impact of turning the problem into a matching problem rather than a pure recognition problem.

Keywords: optical character recognition; OCR; pattern recognition; image processing; warehouse material handling; business rule; data capturing; data integration; logistics; logistics management.

DOI: 10.1504/IJIMS.2019.100986

International Journal of Internet Manufacturing and Services, 2019 Vol.6 No.3, pp.285 - 304

Received: 22 Nov 2017
Accepted: 04 Apr 2018
Published online: 22 Jul 2019 *

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