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.