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This paper presents a novel learning based framework to extract articles from newspaper images using a Fixed-Point Model. The input to the system comprises blocks of text and graphics, obtained using standard image processing techniques. The fixed point model uses contextual information and features of each block to learn the layout of newspaper images and attains a contraction mapping to assign a...
We present a novel word image based document indexing scheme by combination of string matching and hashing. The word image representation is defined by string codes obtained by unsupervised learning over graphical primitives. The indexing framework is defined by distance based hashing function which does the object projection to hash space by preserving their distances. We have used edit distance...
In this paper, we propose a novel framework for segmentation of documents with complex layouts. The document segmentation is performed by combination of clustering and conditional random fields (CRF) based modeling. The bottom-up approach for segmentation assigns each pixel to a cluster plane based on color intensity. A CRF based discriminative model is learned to extract the local neighborhood information...
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