A hybrid text segmentation approach

In this paper, we present a hybrid text segmentation approach for embedded text in images, aiming to combining the advantages of the difference-based methods and the similarity-based methods together. First a new stroke edge filter is applied to obtain stroke edge map. Then a two-threshold method based on the improved Niblack thresholding technique is utilized to identify stroke edges. Those pixels between the edge pairs above the high threshold are collected to estimate the representative of stroke color, so that stroke pixels are further extracted by computing the color similarity. Finally some heuristic rules are devised to integrate stroke edge and stroke region information to obtain better segmentation results. The experimental results show that our approach can effectively segment text from background.