[hal-01142958] AColDPS :Robust and Unsupervised Automatic Color Document Processing System

This paper presents the first fully automatic color analysis system suited for business documents. Our pixel-based approach uses mainly color morphology and does not require any training, manual assistance, prior knowledge or model. We developed a robust color segmentation system adapted for invoices and forms with significant color complexity and dithered background. The system achieves several operations to segment automatically color images, separate text from noise and graphics and provides color information about text color. The contribution of our work is Tree-fold. Firstly, it is the usage of color morphology to simultaneously segment both text and inverted text. Our system processes inverted and non-inverted text automatically using conditional color dilation and erosion, even in cases where there are overlaps between the two. Secondly, it is the extraction of geodesic measures using morphological convolution in order to separate text, noise and graphical elements. Thirdly, we develop a method to disconnect characters touching or overlapping graphical elements. Our system can separate characters that touch straight lines, split overlapped characters with different colors and separate characters from graphics if they have different colors. A color analysis stage automatically calculates the number of character colors. The proposed system is generic enough to process a wide range of images of digitized business documents from different origins. It outperforms the classical approach that uses binarization of greyscale images.



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