Character segmentation on natural images with graph-based representation

Computer vision approaches like shape based descriptors use silhouettes of objects in images. In this paper, a method to extract silhouettes of objects by segmenting images is proposed in order to describe them, especially characters that are obtained from natural images by using shape based descriptors. This method is binary segmentation approach that has a graph-based representation. Dominant intensity values of segments of an image and cut off intensity value to separate those segments are computed dynamically. Thus, characters that have similar dominant intensity value to the background can be segmented as well. Moreover, the performance of the proposed graph based method is compared with the performance of the global thresholding and it is observed that the success of the proposed method is better than the global thresholding.