A text detection method was presented based on support vector machine（SVM） using the statistics features characterizing character strokes.First

our method extracts stroke edges through a modified edge detector;then

candidate text regions are located by merging the regions that contain stroke edges;finally

a 32-dimensional feature is devised to reflect the unique spatial distribution of stroke edges

and the SVM is utilized to model and verify the candidate text re-gions.Our experiments on Chinese characters demonstrate the proposed stroke texture features have good distinction power

especially for text regions composed of many characters。