IEEE Trans Image Process - A unified framework for multioriented text detection and recognition.

Tópicos

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Resumo

High level semantics embodied in scene texts are both rich and clear and thus can serve as important cues for a wide range of vision applications, for instance, image understanding, image indexing, video search, geolocation, and automatic navigation. In this paper, we present a unified framework for text detection and recognition in natural images. The contributions of this paper are threefold: 1) text detection and recognition are accomplished concurrently using exactly the same features and classification scheme; 2) in contrast to methods in the literature, which mainly focus on horizontal or near-horizontal texts, the proposed system is capable of localizing and reading texts of varying orientations; and 3) a new dictionary search method is proposed, to correct the recognition errors usually caused by confusions among similar yet different characters. As an additional contribution, a novel image database with texts of different scales, colors, fonts, and orientations in diverse real-world scenarios, is generated and released. Extensive experiments on standard benchmarks as well as the proposed database demonstrate that the proposed system achieves highly competitive performance, especially on multioriented texts.

Resumo Limpo

high level semant embodi scene text rich clear thus can serv import cue wide rang vision applic instanc imag understand imag index video search geoloc automat navig paper present unifi framework text detect recognit natur imag contribut paper threefold text detect recognit accomplish concurr use exact featur classif scheme contrast method literatur main focus horizont nearhorizont text propos system capabl local read text vari orient new dictionari search method propos correct recognit error usual caus confus among similar yet differ charact addit contribut novel imag databas text differ scale color font orient divers realworld scenario generat releas extens experi standard benchmark well propos databas demonstr propos system achiev high competit perform especi multiori text

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