DISGO: Automatic End-to-End Evaluation for Scene Text OCR

Autor:	Hwang, Mei-Yuh, Shi, Yangyang, Ramchandani, Ankit, Pang, Guan, Krishnan, Praveen, Kabela, Lucas, Seide, Frank, Datta, Samyak, Liu, Jun
Rok vydání:	2023
Předmět:	Computer Science - Computer Vision and Pattern Recognition Computer Science - Computation and Language
Druh dokumentu:	Working Paper
Popis:	This paper discusses the challenges of optical character recognition (OCR) on natural scenes, which is harder than OCR on documents due to the wild content and various image backgrounds. We propose to uniformly use word error rates (WER) as a new measurement for evaluating scene-text OCR, both end-to-end (e2e) performance and individual system component performances. Particularly for the e2e metric, we name it DISGO WER as it considers Deletion, Insertion, Substitution, and Grouping/Ordering errors. Finally we propose to utilize the concept of super blocks to automatically compute BLEU scores for e2e OCR machine translation. The small SCUT public test set is used to demonstrate WER performance by a modularized OCR system. Comment: 9 pages
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2308.13173 Zobrazit plný text záznamu View this record from Arxiv