Energy model based image semantic annotation method
A technology of semantic annotation and energy model, which is applied in semantic analysis, image analysis, image data processing, etc., can solve the problems of reduced annotation accuracy, semantic confusion, and failure to consider spatial constraints, so as to avoid semantic confusion and improve accuracy.
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[0078] The present invention will be described in detail below in conjunction with specific embodiments.
[0079] An image semantic annotation method based on an energy model, comprising:
[0080] (1) Divide the original image into several regional images, and extract the visual feature vectors of each regional image.
[0081] In this embodiment, the visual feature fuzzy c-means (FCM) clustering algorithm is used to segment the original image and extract the visual feature vectors of the images in each region. The visual feature vector can be a feature vector based on the Moving Picture Experts Group-7 (MPEG-7) feature, or a feature vector based on the scale-invariant feature transform (Scale-invariant feature transform, SIFT) A feature vector, in this embodiment, is a feature vector based on SIFT features.
[0082] (2) According to the visual feature vector of each region, use the trained SVM classifier to determine the candidate semantic labels of each region image, and th...
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