Locating text in complex color images

Abstract

There is a substantial interest in retrieving images from a large database using the textual information contained in the images. An algorithm which will automatically locate the textual regions in the input image will facilitate this task; the optical character recognizer can then be applied to only those regions of the image which contain text. We present two methods for automatically locating text in complex color images. The first method segments the image into connected components with uniform color, and uses several heuristics (size, alignment, proximity) to select the components which are likely to contain character(s) belonging to the text. The second method computes the local spatial variation in the gray-scale image, and locates text in regions with high variance. A combination of the two approaches is shown to be more effective than the individual methods. The proposed methods have been used to locate text in compact disc (CD) and book cover images, as well as in the images of traffic scenes captured by a video camera. Initial results are encouraging and suggest that these algorithms can be used in image retrieval applications.