ICDAR 2021 Competition on Integrated Circuit Text Spotting and Aesthetic Assessment
Chun Chet Ng, Akmalul Khairi Bin Nazaruddin, Yeong Khang Lee, Xinyu, Wang, Yuliang Liu, Chee Seng Chan, Lianwen Jin, Yipeng Sun, and Lixin Fan

TL;DR
This paper introduces the RRC-ICText 2021 challenge, focusing on improving text detection and aesthetic assessment on chip components, supported by the ICText dataset, to advance research in electronic chip inspection.
Contribution
It presents a new competition and dataset for integrated circuit text spotting and aesthetic assessment, fostering progress in this specialized area.
Findings
233 submissions from 10 teams/individuals
Detailed analysis of competition results
Encourages research on chip text inspection
Abstract
With hundreds of thousands of electronic chip components are being manufactured every day, chip manufacturers have seen an increasing demand in seeking a more efficient and effective way of inspecting the quality of printed texts on chip components. The major problem that deters this area of research is the lacking of realistic text on chips datasets to act as a strong foundation. Hence, a text on chips dataset, ICText is used as the main target for the proposed Robust Reading Challenge on Integrated Circuit Text Spotting and Aesthetic Assessment (RRC-ICText) 2021 to encourage the research on this problem. Throughout the entire competition, we have received a total of 233 submissions from 10 unique teams/individuals. Details of the competition and submission results are presented in this report.
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Taxonomy
TopicsHandwritten Text Recognition Techniques · Image Retrieval and Classification Techniques · Advanced Image and Video Retrieval Techniques
