Document layout analysis

In computer vision or natural language processing, document layout analysis is the process of identifying and categorizing the regions of interest in the scanned image of a text document. A reading system requires the segmentation of text zones from non-textual ones and the arrangement in their correct reading order. Detection and labeling of the different zones (or blocks) as text body, illustrations, math symbols, and tables embedded in a document is called geometric layout analysis. But text zones play different logical roles inside the document (titles, captions, footnotes, etc.) and this kind of semantic labeling is the scope of the logical layout analysis. Document layout analysis is the union of geometric and logical labeling. It is typically performed before a document image is sent to an OCR engine, but it can be used also to detect duplicate copies of the same document in large archives, or to index documents by their structure or pictorial content. Document layout is formally defined in the international standard ISO 8613-1:1989.

In computer vision or natural language processing, document layout analysis is the process of identifying and categorizing the regions of interest in the scanned image of a text document. A reading system requires the segmentation of text zones from non-textual ones and the arrangement in their correct reading order. Detection and labeling of the different zones (or blocks) as text body, illustrations, math symbols, and tables embedded in a document is called geometric layout analysis. But text zones play different logical roles inside the document (titles, captions, footnotes, etc.) and this kind of semantic labeling is the scope of the logical layout analysis. Document layout analysis is the union of geometric and logical labeling. It is typically performed before a document image is sent to an OCR engine, but it can be used also to detect duplicate copies of the same document in large archives, or to index documents by their structure or pictorial content. Document layout is formally defined in the international standard ISO 8613-1:1989. For each symbol, determine its k nearest neighbors where k is an integer greater than or equal to four. O`Gorman suggests k=5 in his paper as a good compromise between robustness and speed. The reason to use at least k=4 is that for a symbol in a document, the two or three nearest symbols are the ones right next to it on the same text line. The fourth-nearest symbol is typically on a line right above or below, and it is important to include these symbols in the nearest neighbor calculation for the following. Each nearest neighbor pair of symbols is related by a vector pointing from one symbol's centroid to the other symbol's centroid. If these vectors are plotted for every pair of nearest neighbor symbols, then one gets what is called the docstrum for the document (See figure below). One can also use the angle Θ from the horizontal and distance D between two nearest neighbor symbols and create a nearest-neighbor angle and nearest-neighbor distance histogram. Using the nearest-neighbor angle histogram, the skew of the document can be calculated. If the skew is acceptably low, continue to the next step. If it is not, rotate the image so as to remove the skew and return to step 3. The nearest-neighbor distance histogram has several peaks, and these peaks typically represent between-character spacing, between-word spacing, and between-line spacing. Calculate these values from the histogram and set them aside. For each symbol, look at its nearest neighbors and flag any of them that are a distance away which is within some tolerance of the between-character spacing distance or between-word spacing distance. For each nearest neighbor symbol which is flagged, draw a line segment connecting their centroids. Symbols connected to their neighbors by line segments form text lines. Using all the centroids in a text line, one can compute an actual line segment representing the text line with linear regression. This is important because it is unlikely that all the centroids of symbols in a text line are actually collinear. For each pair of text lines, one can compute a minimum distance between their corresponding line segments. If this distance is within some tolerance of the between-line spacing calculated in step 7, then the two text lines are grouped into the same text block. Finally, one can calculate a bounding box for each text block, and the document layout analysis is complete. ==See also== Document processing Open Document Architecture ==References== ==Further reading== ==External links== Apostille For Documents High Performance Document Layout Analysis by Thomas M. Breuel, at PARC, Palo Alto, CA, USA, 2003 Geometric Layout Analysis Techniques for Document Image Understanding: a Review, ITC-irst Technical Report TR#9703-09, 1998.

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