caa a22 4500 605447403 CHVBK 20210128100132.0 cr unu---uuuuu 210128e20150701xx s 000 0 eng 10.1007/s11042-014-1858-9 doi (NATIONALLICENCE)springer-10.1007/s11042-014-1858-9 Bayesian network based semantic image classification with attributed relational graph [Elektronische Daten] [Chang-Yong Ri, Min Yao] Semantic image classification is a hot issue of image mining. Information of spatial relations between objects in an image is one of the important semantic information of an image. However, the previous researches have not made full use of the spatial relations for image modeling and classification. In addition, to classify the images with Bayesian network, the accuracy of conditional probability estimation may be insufficient, because the learning methods of spatial contextual models have usually used a limited number of training samples. In this work, the semantic image modeling based on attributed relational graph has been proposed, in which the distance measure method between images was presented, therefore the object information and spatial relational information could be fully utilized. Then, the semantic distance between images based on attributed relational graph could be calculated for the support vector machine to obtain the joint conditional probability distribution of Bayesian network. Therefore the probabilistic estimation problem under the sparse training samples could be solved, and the accuracy of semantic image classification with Bayesian network was improved. Experimental results show the validity and reliability of this proposed method. Springer Science+Business Media New York, 2014 Semantic image classification nationallicence Attributed relational graph nationallicence Semantic distance nationallicence Bayesian network nationallicence Ri Chang-Yong School of Computer Science and Technology, Zhejiang University, 310027, Hangzhou, China aut Yao Min School of Computer Science and Technology, Zhejiang University, 310027, Hangzhou, China aut Multimedia Tools and Applications Springer US; http://www.springer-ny.com 74/13(2015-07-01), 4965-4986 1380-7501 74:13<4965 2015 74 11042 https://doi.org/10.1007/s11042-014-1858-9 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s11042-014-1858-9 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Ri Chang-Yong School of Computer Science and Technology, Zhejiang University, 310027, Hangzhou, China aut NATIONALLICENCE 700 1- Yao Min School of Computer Science and Technology, Zhejiang University, 310027, Hangzhou, China aut NATIONALLICENCE 773 0- Multimedia Tools and Applications Springer US; http://www.springer-ny.com 74/13(2015-07-01), 4965-4986 1380-7501 74:13<4965 2015 74 11042