In this paper, we propose an algorithm for extracting text regions from spam-mail images using color layer. The CLTE(color layer-based text extraction) divides the input image into eight planes as color layers. It extracts connected components on the ...
In this paper, we propose an algorithm for extracting text regions from spam-mail images using color layer. The CLTE(color layer-based text extraction) divides the input image into eight planes as color layers. It extracts connected components on the eight images, and then classifies them into text regions and non-text regions based on the component sizes. We also propose an algorithm for recovering damaged text strokes from the extracted text image. In the binary image, there are two types of damaged strokes: (1) middle strokes such as 'ㅣ' or 'ㅡ' are deleted, and (2) the first and/or last strokes such as 'ㅇ' or 'ㅁ' are filled with black pixels. An experiment with 200 spam-mail images shows that the proposed approach is more accurate than conventional methods by over 10%.