Layouts and sub-layouts constitute an important clue while searching a document on the basis of its structure, or when textual content is unknown irrelevant. A sub-layout specifies the arrangement of document entities within a smaller portion of the document. We propose an efficient graph-based matching algorithm, integrated with hash-based indexing, to prune a possibly large search space. A user can specify a combination of sub-layouts of interest using sketch-based queries. The system supports partial matching for unspecified layout entities. We handle cases of segmentation pre-processing errors (for text non-text blocks) with a symmetry maximization-based strategy, and accounting for multiple domain-specific plausible segmentation hypotheses. We show promising results of our system on a database of unstructured entities, containing 4776 newspaper images.
van @cite_5 use layout information for document retrieval. A class of distance measure based on two-step procedure is introduced. In the first step, the distances between the blocks of document and query layouts are calculated. Various types of distance measures like, Manhattan distance of corner points, overlapping area of blocks, difference in width and height, etc., were used to compute distance between every pair of blocks in given layouts. Then, the matching step matches the blocks of query layout to the blocks of reference layout by minimizing the total distance. Since the method uses distance measure, it is not invariant to position and shape of the blocks. Besides, the number of blocks in case of sub-layouts will be lesser and their position and aspect ratios can be different, the total distance between two layouts will be larger and thus, may not match.
@cite_5
2170288539
Most methods for document image retrieval rely solely on text information to find similar documents. This paper describes a way to use layout information for document image retrieval instead. A new class of distance measures is introduced for documents with Manhattan layouts, based on a two-step procedure: First, the distances between the blocks of two layouts are calculated. Then, the blocks of one layout are assigned to the blocks of the other layout in a matching step. Different block distances and matching methods are compared and evaluated using the publicly available MARG database. On this dataset, the layout type can be determined successfully in 92.6 of the cases using the best distance measure in a nearest neighbor classifier. The experiments show that the best distance measure for this task is the overlapping area combined with the Manhattan distance of the corner points as block distance together with the minimum weight edge cover matching.