Method and device for identifying closed regions

Abstract

The invention relates to a method and device for identifying closed regions. The method and device are used for accurately identifying the closed regions in a file. The method comprises the steps that binarization is conducted on input images containing the closed regions, and binary images are obtained; the binary images are scanned to determine candidate regions; all points in the candidate regions are sequentially scanned, and a category label is added to each point in the mode that the points adjacent to the point are scanned, if one of the points adjacent to the point has been provided with the category label, the smallest value in the category label of the point adjacent to the point is distributed to the category label of the point, and if no point with category label exists in the points adjacent to the point, the value of the category label is increased progressively by 1, and the new category label value is distributed to the category label; the points with the same category label value are identified to belong to the same region. Even if the closed regions are connected, all the closed regions can still be extracted through the method, and it has nothing to do with the shapes and widths of lines marking the regions.

Description

technical field [0001] The present invention relates to image processing technology, and more particularly, to a closed area recognition method and device. Background technique [0002] People usually mark things of interest as they read documents. Therefore, some methods are proposed to extract marked regions in documents. However, some methods cannot accurately separate multiple connected regions. Some methods can extract multiple regions, but they cannot be extracted precisely when these regions are connected to each other. Some other methods are based on graph methods to extract connected closed regions, but these methods also cannot extract closed regions precisely. [0003] Methods have also been proposed which may require knowledge of the shape of the marked regions in order to extract closed regions. Some extraction methods only work on regions of a certain shape. For example, some methods are only able to extract regions of rectangular shape. Obviously, this l...

AI Technical Summary

Problems solved by technology

However, this method cannot accurately extract closed areas, nor does it support the situation where multiple areas are connected

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