2025/12/23 by Sneha Oommen, Oommen, Sneha, Gabby Sanchez +9
Arts and Humanities · Computer Science · #Data Visualization and Analytics #Digital Humanities and Scholarship #FOS: Computer and information sciences #Handwritten Text Recognition Techniques #Information Retrieval (cs.IR) #Software Engineering (cs.SE)
paper · doi:10.48550/arxiv.2512.19958
openalex publication_date 2025/12/23 · openalex created_date 2025/12/25 · openalex updated_date 2026/07/28
This paper presents an evaluation of the AWS Textract in the context of extracting data from receipts. We analyse Textract functionalities using a dataset that includes receipts of varied formats and conditions. Our analysis provided a qualitative view of Textract strengths and limitations. While the receipts totals were consistently detected, we also observed typical issues and irregularities that were often influenced by image quality and layout. Based on the analysis of the observations, we propose mitigation strategies.