Form feature describing and indexing method of image object

Abstract

The invention discloses a form feature describing and indexing method of an image object, which comprises the following steps of: inputting a to-be-indexed image object P of a binary image form; carrying out form feature extraction on the to-be-indexed image object P; calculating the similarity of the to-be-indexed image object P and a to-be-compared image object Q in a system example base on thebasis of the form feature description expressed by each layer of image object; and selecting one example or one group of examples with highest similarity with the to-be-indexed image object P as an index result to be output from the system example base. The form feature description integrates form features of multiple layers of image objects, has better describing and indexing property, is flexible and adjustable in the indexing precision and the algorithm complexity, can adapt the processing demands of a larger range of object types, can effectively process the influences of interference conditions of noise, local deformation and the like in the image indexing, and is suitable for various image indexing and recognition processing software systems.

Description

technical field [0001] The invention relates to a graphic object processing method in the technical field of computer software, in particular to a shape feature description and retrieval method of a graphic object used in a system involving graphic data retrieval and recognition processing. Background technique [0002] Graphics are an important type of visual information that people are exposed to daily, and are widely used to convey information that is difficult to express in words. Examples of graphics include various graphic symbols, characters, and marks as small as various types such as maps, sketches, and engineering drawings. With the development of science and technology, especially the development of computing, interaction and display technology, graphics are applied in more and more fields, and at the same time, a large amount of graphic data is constantly growing. In order to enable people to use graphic data and the information contained in it efficiently and c...

AI Technical Summary

Problems solved by technology

However, for conventional image retrieval requirements, the establishment of 3D models has high difficulty and complexity

[0007] Based on the above classification of graphic feature description methods, the retrieval or recognition methods relying on a single feature description reflect the effectiveness of a specific class of problems, but also have certain limitations, mainly manifested in comparison with complex and changeable image features. For graphic objects, a single feature representation or modeling method cannot cover enough characterization and differentiation information, thus affecting the performance of graphic recognition and retrieval systems based on these feature modeling methods when dealing with general types of graphic objects and coping with noise and other interference factors Performance

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