An Automatic Classification Algorithm of Digital Image Based on Semantics

Abstract: The randomness and fuzziness of digital image semantics are hot issues in the field of classification technology, so a new semantic representation of digital image based on cloud model is proposed and a semantic vector space is constructed. In the space, semantic classifications of digital images are completed by calculating the semantic class certainty degree (SCCD). In addition, we propose cloud support vector machine based on image semantics (CSVM-IS) model, which can effectively utilize the knowledge of SCCD. At the same time, CSVM-IS can automatically and effectively classify the multi-semantic information and eliminate the rejection of the classification samples. We design two kinds of simulation experiments to verify the classification performance. One experiment is to verify the classification accuracy, and the other is to verify the classification effectiveness. Experimental results show that CSVM-IS is superior to the Nesting Algorithm in terms of classification performance.