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Text detection and segmentation is an important prerequisite for many contentbased image analysis tasks. The paper proposes a novel text extraction andcharacter segmentation algorithm using Maximally Stable Extremal Regions asbasic letter candidates. These regions are then subjected to thresholding andthereafter various connected components are determined to identify separatecharacters. The algorithm is tested along a set of various JPEG, PNG and BMPimages over four different character sets; English, Russian, Hindi and Urdu.The algorithm gives good results for English and Russian character set; howevercharacter segmentation in Urdu and Hindi language is not much accurate. Thealgorithm is simple, efficient, involves no overhead as required in trainingand gives good results for even low quality images. The paper also proposesvarious challenges in text extraction and segmentation for multilingual inputs.

Automatic text extraction and character segmentation using maximally stable extremal regions