A Method of Automatic Image Annotation Based on Semantic Scene Classification

Abstract

The invention belongs to the field of computer application and computational vision, and relates to an image automatic tagging algorithm based on semantic scene classification. This method uses the method based on non-negative matrix decomposition to detect the semantic scene information of the label, maps the training set samples to the corresponding scenes in a probabilistic manner, and uses the scene information of the samples to train the scene classifier based on the extreme learning machine and the differential evolution algorithm. Finally, the scene classifier is used to quickly map the samples to be labeled to a sample subset related to its scene, and the KNN-based algorithm is used to complete the labeling in this sample subset. The invention not only narrows the scope of searching for the nearest neighbor samples and improves the efficiency of the algorithm, but also enables the KNN algorithm to label semantically related sample sets, thereby reducing noise interference and improving the labeling effect. The number of scenes in this method is far less than the number of labels, so it solves the problem that the method based on model learning is not suitable for data sets with a large number of labels.

Description

technical field [0001] The invention relates to the fields of computer application and computer vision, and relates to an automatic image labeling algorithm based on semantic scene classification. Background technique [0002] It is a common and relatively simple and effective way to manage and retrieve images through image tags, but there are still a large number of unlabeled or incompletely labeled images on the Internet, so designing an effective automatic image labeling and classification algorithm is a solution to this problem. The key technology of the problem. In recent years, there has been a lot of research work on the problem of automatic image annotation. The main research methods can be divided into two categories: methods based on model learning and methods based on searching databases. [0003] The method based on searching the database directly provides label candidate sequences according to the labels of the marked images in the database, which is simple an...

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Problems solved by technology

[0008] Aiming at the problem of not considering the mapping relationship between tags and semantic scenes and the existing hard classification of tags in the image tagging problem, the present invention proposes an automatic image tagging method based on semantic scene classification

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