Multi-classifier integration-based image character recognition method

Abstract

The invention provides a multi-classifier integration-based image character recognition method. The method comprises the following steps of: converting a colored to-be-identified image into a grayscale image; carrying out binary processing on the grayscale image and segmenting an image region with character information; segmenting each Chinese character from a whole character image; extracting grid features and direction features of each Chinese character; selecting stroke density total length features to carry out first-layer rough classification by adoption of a minimum distance classifier; and respectively selecting peripheral features, the grid features and the direction features to complete second-layer classification matching by adoption of a nearest-neighbor classifier. The method has the advantages that the character recognition has relatively strong anti-jamming capability and relatively strong character local structure description capability, and is less influenced by stroke widths; by adoption of a classifier integration technology of complementing and combining the minimum distance classifier and the nearest-neighbor classifier, a system is more reliable; and the characters can be intelligently recognized, so that the adaptability of the system is improved and the recognition rate is high.

Description

technical field [0001] The present invention relates to the field of image and character recognition, and more specifically, relates to an image and character recognition method based on multi-classifier integration. Background technique [0002] Social development has entered the information age. With the expansion and deepening of practical activities and the needs of socialization, human beings need to identify many types of information with complex forms and contents. People no longer stay in their own ears and eyes to directly obtain this information, but use computers to automatically input text into computers. Due to the continuous improvement of the level of science and technology, various research objects have been "imaged" and "digitized", and multimedia information based on images has quickly become an important information transmission medium. The text information in the image contains rich high-level semantic information. . Extracting these words is very helpf...

AI Technical Summary

Problems solved by technology

[0003] Now, there are still several problems in the research of text image recognition technology. One is the large amount of image data. Generally speaking, to obtain higher recognition accuracy, the original image should have a higher resolution, at least larger than 64×64

The second is image defacement, which will deface the image due to the interference of the target environment, transmission errors, sensor errors, noise, background interference, deformation, etc.

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