Automatic identification and skew estimation of text lines in real scene images

A method for the automatic localization of text embedded in complex images is proposed. It permits to detect the spatial position and the skew of the text lines which are present in the scene and to return a binary representation of each text line. Strenghts of the algorithm are independece of text skew and of presence of connected text. After a preprocessing step the input image is segmented in order to obtain a set of connected components which represent the basic objects of the algorithm. Several heuristics are proposed to characterize text objects which depend both on the geometrical features of single components and on the geometrical and spatial relations among components. According to these heuristics several components are discarded and the retained ones are grouped into text lines candidates by means of a divisive hierachical clustering procedure. In the experimental session we describe the application of the algorithm to the extraction of text lines from the images of 100 book covers. Results about skew estimation are also reported.