A knowledge-based system for extracting text-lines from mixed and overlapping text/graphics compound document images

This paper presents a new knowledge-based system for extracting and identifying text-lines from various real-life mixed text/graphics compound document images. The proposed system first decomposes the document image into distinct object planes to separate homogeneous objects, including textual regions of interest, non-text objects such as graphics and pictures, and background textures. A knowledge-based text extraction and identification method obtains the text-lines with different characteristics in each plane. The proposed system offers high flexibility and expandability by merely updating new rules to cope with various types of real-life complex document images. Experimental and comparative results prove the effectiveness of the proposed knowledge-based system and its advantages in extracting text-lines with a large variety of illumination levels, sizes, and font styles from various types of mixed and overlapping text/graphics complex compound document images.

► We propose a knowledge-based system for extracting and identifying text-lines from compound document images.
► The document image is decomposed into distinct object planes to separate homogeneous objects.
► A knowledge-based text extraction and identification method obtains the text-lines with different characteristics in each plane.
► The proposed system offers high flexibility and expandability by updating new rules to cope with various complex document images.