International phonetic sign typeface identification method based on feature matching

Abstract

The invention provides an international phonetic sign typeface identification method based on feature matching, and relates to the technical field of typeface identification. The method comprises the following steps that international phonetic sign images with the unified dimension are subjected to preprocessing, i.e., each international phonetic sign image is subjected to fining processing, the typeface part in the image is scanned line by line under the condition of ensuring that the continuity of the typeface pixel is not interfered, further, excessive pixel points are removed, and the preprocessed international phonetic sign typeface images are obtained; feature points are extracted; the feature points of each training typeface sample are used for building a template base; input typeface images are tested, feature points are matched, and test results are obtained. The method provided by the invention is utilized, the correct identification on the international phonetic sign typeface can be carried out through the feature point matching, simplicity and high efficiency are realized, in addition, the method can also be used in the typeface identification of other languages, and the universality is good.

Description

technical field [0001] The invention relates to the technical field of font recognition, in particular to a method for recognizing fonts in the International Phonetic Alphabet based on feature extraction. Background technique [0002] At present, the analysis of printed text involves the font recognition of the content. Although the optical character recognition technology is very mature, it rarely considers the multi-font text. Adding the font recognition module to the optical character recognition device can greatly improve the text recognition efficiency and classification results. In view of the widespread use of the International Phonetic Alphabet, and the lack of functional modules for identifying IPA fonts in the optical character system, it is very necessary to propose a simple and high-accuracy method to realize font recognition. [0003] In the prior art solutions, most of them use texture features and typesetting features for feature analysis. The process of fea...

AI Technical Summary

Problems solved by technology

The process of feature extraction through texture is complicated, and the entire text area needs to be processed, and the blank area between the text is removed as a preprocessing operation for feature extraction, and then Gabor filter, wavelet transform or other techniques are used for feature extraction. The process cumbersome

Although the features extracted through typesetting characteristics can represent the characteristics of fonts, the anti-noise performance is not high, and fo...

Images