Finding Text Regions Using Localised Measures

Paul Clark, Majid Mirmehdi, Finding Text Regions Using Localised Measures. Proceedings of the 11th British Machine Vision Conference. Majid Mirmehdi, Barry Thomas, (eds.). ISBN 1 901725 13 8, pp. 675–684. September 2000. PDF, 783 Kbytes.

Abstract

We present a method based on statistical properties of local image neighbourhoods for the location of text in real-scene images. This has applications in robot vision, and desktop and wearable computing. The statistical measures we describe extract properties of the image which characterise text, invariant to a large degree to the orientation, scale or colo ur of the text in the scene. The measures are employed by a neural network to classify regions of an image as text or non-text. We thus avoid the use of different thresholds for the various situations we expect, including when text is too small to read, or when the text plane is not fronto-parallel to the camera. We briefly discuss applications and the possibility of recovery of the text for optical character recognition.

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