Method of classifying Naive Bayes scanned certificate images based on feature weighting

Abstract

The invention discloses a method of classifying Naive Bayes scanned certificate images based on feature weighting. The method comprises the steps of carrying out round seal locating, dividing and sizing on certificate images processed, and extracting color feature vectors of an HSV (Hue, Saturation, Value) space of a round seal area and the length-width ratio of the images; building a certificate image database, processing each certificate image in the database according to the above steps, so as to obtain the round seal HSV color feature vector and the length-width ratio of each scanned certificate image in the data base, calculating the probability of different data combinations in the certificate image database according to the obtained feature vectors, and storing the data after the feature weighting; calculating an image category which is most possible to appear according to a Naive Bayes algorithm and the probability of different data combinations in the certificate image database, and judging the classification of the images when the probability meets a set threshold requirement. According to the method, the certificate images can be simply and quickly classified, and the certificate image retrieval efficiency can be improved.

Description

technical field [0001] The invention relates to an image classification method, in particular to a scanning certificate image classification method. Background technique [0002] In recent years, image retrieval is a very popular topic, and its retrieval objects include objects swimming in the sea, flying in the sky and walking on the ground. Image classification is a preprocessing process of image retrieval, which can effectively improve the accuracy of image retrieval. Although there are many image classification and retrieval systems for different kinds of image datasets, less attention has been paid to the classification and retrieval of scanned certificate images, which are often important auxiliary materials for applications for awards or company expansion. In order to ensure the legitimate use of such certificate images and avoid multiple use of the same certificate, it is very important for some retrieval systems to check the scanned images in the special scanned ce...

AI Technical Summary

Problems solved by technology

At present, the image features suitable for the popular content-based image classification retrieval system include color, texture, shape and spatial position relationship, but the image quality of the scanned certificate is low, there are many types, and the layout forms are diverse, including image signs with specific meanings, At the same time, it also contains a concise description of the award-winning situation. Therefore, it is difficult to find whether there is an image file similar to the certificate to be tested from the massive image library only by using the existing algorithm.

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