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Reading Text in Consumer Digital Photographs

机译:阅读消费者数码照片中的文字

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摘要

We present a distributed system to extract text contained in natural scenes within consumer photographs. The objective is to automatically annotate pictures in order to make consumer photo sets searchable based on the image content. The system is designed to process a large volume of photos, by quickly isolating candidate text regions, and successively cascading them through a series of text recognition engines which jointly make a decision on whether or not the region contains text that is readable by OCR. In addition, a dedicated rejection engine is built on top of each text recognizer to adapt its confidence measure to the specifics of the task. The resulting system achieves very high text retrieval rate and data throughput with very small false detection rates.
机译:我们提出了一种分布式系统,用于提取消费者照片中自然场景中包含的文本。目的是自动注释图片,以使用户图片集可基于图像内容进行搜索。该系统设计为通过快速隔离候选文本区域并通过一系列文本识别引擎依次层叠它们来处理大量照片,这些文本识别引擎共同决定该区域是否包含OCR可读的文本。此外,在每个文本识别器的顶部都建立了专用的拒绝引擎,以使其置信度度量适应任务的具体要求。最终的系统以非常小的错误检测率实现了很高的文本检索率和数据吞吐量。

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