Mridul Ghosh, Himadri Mukherjee, Sk Md Obaidullah, Xiao-Zhi Gao, Kaushik Roy
{"title":"Scene text understanding: recapitulating the past decade","authors":"Mridul Ghosh, Himadri Mukherjee, Sk Md Obaidullah, Xiao-Zhi Gao, Kaushik Roy","doi":"10.1007/s10462-023-10530-3","DOIUrl":null,"url":null,"abstract":"<div><p>Computational perception has indeed been dramatically modified and reformed from handcrafted feature-based techniques to the advent of deep learning. Scene text identification and recognition have inexorably been touched by this bow effort of upheaval, ushering in the period of deep learning. It is an important aspect of machine vision. Society has seen significant improvements in thinking, approach, and effectiveness over time. The goal of this study is to summarize and analyze the important developments and notable advancements in scene text identification and recognition over the past decade. We have discussed the significant handcrafted feature-based techniques which had been regarded as flagship systems in the past. They were succeeded by deep learning-based techniques. We have discussed such approaches from their inception to the development of complex models which have taken scene text identification to the next stage.</p></div>","PeriodicalId":8449,"journal":{"name":"Artificial Intelligence Review","volume":"56 12","pages":"15301 - 15373"},"PeriodicalIF":10.7000,"publicationDate":"2023-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Artificial Intelligence Review","FirstCategoryId":"94","ListUrlMain":"https://link.springer.com/article/10.1007/s10462-023-10530-3","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 1
Abstract
Computational perception has indeed been dramatically modified and reformed from handcrafted feature-based techniques to the advent of deep learning. Scene text identification and recognition have inexorably been touched by this bow effort of upheaval, ushering in the period of deep learning. It is an important aspect of machine vision. Society has seen significant improvements in thinking, approach, and effectiveness over time. The goal of this study is to summarize and analyze the important developments and notable advancements in scene text identification and recognition over the past decade. We have discussed the significant handcrafted feature-based techniques which had been regarded as flagship systems in the past. They were succeeded by deep learning-based techniques. We have discussed such approaches from their inception to the development of complex models which have taken scene text identification to the next stage.
期刊介绍:
Artificial Intelligence Review, a fully open access journal, publishes cutting-edge research in artificial intelligence and cognitive science. It features critical evaluations of applications, techniques, and algorithms, providing a platform for both researchers and application developers. The journal includes refereed survey and tutorial articles, along with reviews and commentary on significant developments in the field.