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A novel stock counting system for detecting lot numbers using Tesseract OCR
Counting stock is one of the warehouse’s methods for preventing insatiable stock. Moreover, it could help the company forecast how many products they need to store and predict the replenished goods for customers. However, stock count in the medical business, which sells specialized medical equipment...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Nature Singapore
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9540281/ https://www.ncbi.nlm.nih.gov/pubmed/36246341 http://dx.doi.org/10.1007/s41870-022-01107-4 |
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author | Lertsawatwicha, Parkpoom Phathong, Phumidon Tantasanee, Napatsorn Sarawutthinun, Kotchakorn Siriborvornratanakul, Thitirat |
author_facet | Lertsawatwicha, Parkpoom Phathong, Phumidon Tantasanee, Napatsorn Sarawutthinun, Kotchakorn Siriborvornratanakul, Thitirat |
author_sort | Lertsawatwicha, Parkpoom |
collection | PubMed |
description | Counting stock is one of the warehouse’s methods for preventing insatiable stock. Moreover, it could help the company forecast how many products they need to store and predict the replenished goods for customers. However, stock count in the medical business, which sells specialized medical equipment, needs more focus on, because it uses to treat the patient. So that lack of inventory should not happen. In a normal situation, stock count at some hospitals is quite hard for salespeople, especially hospitals in upcountry that far away. During the COVID-19 situation, many limits need to be strict. At this point, it causes a shortage of goods in many hospitals. In this paper, we represent how computer vision can help this process. When the hospital’s officer sends images of stock to our system. The system will recognize the quantity and lot number of goods that remain in the hospital. Therefore, salespeople can decrease the times to visit hospitals. The result showed that for text detection and text recognition in a specific use case. Our prototype system achieves 84.17% in accuracy. |
format | Online Article Text |
id | pubmed-9540281 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer Nature Singapore |
record_format | MEDLINE/PubMed |
spelling | pubmed-95402812022-10-11 A novel stock counting system for detecting lot numbers using Tesseract OCR Lertsawatwicha, Parkpoom Phathong, Phumidon Tantasanee, Napatsorn Sarawutthinun, Kotchakorn Siriborvornratanakul, Thitirat Int J Inf Technol Original Research Counting stock is one of the warehouse’s methods for preventing insatiable stock. Moreover, it could help the company forecast how many products they need to store and predict the replenished goods for customers. However, stock count in the medical business, which sells specialized medical equipment, needs more focus on, because it uses to treat the patient. So that lack of inventory should not happen. In a normal situation, stock count at some hospitals is quite hard for salespeople, especially hospitals in upcountry that far away. During the COVID-19 situation, many limits need to be strict. At this point, it causes a shortage of goods in many hospitals. In this paper, we represent how computer vision can help this process. When the hospital’s officer sends images of stock to our system. The system will recognize the quantity and lot number of goods that remain in the hospital. Therefore, salespeople can decrease the times to visit hospitals. The result showed that for text detection and text recognition in a specific use case. Our prototype system achieves 84.17% in accuracy. Springer Nature Singapore 2022-10-06 2023 /pmc/articles/PMC9540281/ /pubmed/36246341 http://dx.doi.org/10.1007/s41870-022-01107-4 Text en © The Author(s), under exclusive licence to Bharati Vidyapeeth's Institute of Computer Applications and Management 2022, Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Original Research Lertsawatwicha, Parkpoom Phathong, Phumidon Tantasanee, Napatsorn Sarawutthinun, Kotchakorn Siriborvornratanakul, Thitirat A novel stock counting system for detecting lot numbers using Tesseract OCR |
title | A novel stock counting system for detecting lot numbers using Tesseract OCR |
title_full | A novel stock counting system for detecting lot numbers using Tesseract OCR |
title_fullStr | A novel stock counting system for detecting lot numbers using Tesseract OCR |
title_full_unstemmed | A novel stock counting system for detecting lot numbers using Tesseract OCR |
title_short | A novel stock counting system for detecting lot numbers using Tesseract OCR |
title_sort | novel stock counting system for detecting lot numbers using tesseract ocr |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9540281/ https://www.ncbi.nlm.nih.gov/pubmed/36246341 http://dx.doi.org/10.1007/s41870-022-01107-4 |
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