We present two different approaches to the location and recovery of text in images of real scenes. The techniques we describe are invariant to the scale and 3D orientation of the text, and allow recovery of text in cluttered scenes. The first approach uses page edges and other rectangular boundaries around text to locate a surface containing text, and to recover a fronto-parallel view. This is performed using line detection, perceptual grouping, and comparison of potential text regions using a confidence measure. The second approach uses low-level texture measures with a neural network classifier to locate regions of text in an image. Then we recover a fronto-parallel view of each located paragraph of text by separating the individual lines of text and determining the vanishing points of the text plane. We illustrate our results using a number of images.
|Translated title of the contribution||Recognising text in real scenes|
|Pages (from-to)||243 - 257|
|Number of pages||14|
|Journal||International Journal on Document Analysis and Recognition|
|Publication status||Published - Aug 2002|