Chinese painting image identifying method based on local semantic concept

Abstract

The invention relates to a Chinese painting image identifying method based on a local semantic concept, which comprises the following steps: 1) collecting the image of a Chinese painting works to be identified by using a scanning device and storing the image into a computer; 2) dividing the collected image of the Chinese painting works into a training sample set and a testing sample set by using a random withdrawal device; 3) respectively extracting an obvious area image from the image of the Chinese painting works from the training sample set and the testing sample set by using a visual attention model; 4) establishing an image word-packaging model of the Chinese painting works for the image of the Chinese painting works and corresponding obvious area image in the training sample set; 5) generating two corresponding spatial pyramid feature column diagrams according to the image word-packaging model and a spatial pyramid model; 6) confusing the two spatial pyramid feature column diagrams generated in step 5) by using a serial confusing method; and 7) identifying the Chinese painting image to be identified in the testing sample set by using more than one classifying method of clustering method, K nearest neighbor method, neural network method and support vector machine method, and outputting an identifying result in the manner of identifying accuracy rate and confusion matrix.

Description

technical field [0001] The invention relates to an image recognition method, in particular to a traditional Chinese painting image recognition method based on local semantic concepts. Background technique [0002] In recent years, semantic-based image classification and annotation technology has become a research hotspot closely related to CBIR (Content-Based Image Retrieval). Performance, and can bridge the "semantic gap" to a certain extent. Different from traditional digital images, the semantic information covered by traditional Chinese paintings is richer and more abstract. If the automatic classification and labeling of Chinese painting images can be realized, it can be widely used in the field of digital calligraphy and painting museums, and become a key technology in major research projects such as digital libraries. [0003] The purpose of image scene classification is to classify the image as a whole into a certain scene category. Most of the existing research w...

AI Technical Summary

Problems solved by technology

However, for the image sample library with a large background area, the classification results will be biased.

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