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Image marking method based on characteristic scene

A feature scene, image annotation technology, applied in special data processing applications, instruments, electronic digital data processing and other directions, can solve the problem of inability to guarantee semantic content consistency, to ensure semantic consistency, increase consistency, and improve reliability. Effect

Inactive Publication Date: 2012-02-01
HARBIN ENG UNIV
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AI Technical Summary

Problems solved by technology

[0003] For scene classification of learning images, relying only on the visual features of images obviously cannot guarantee the consistency of semantic content

Method used

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  • Image marking method based on characteristic scene
  • Image marking method based on characteristic scene

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Embodiment Construction

[0020] Combine below figure 1 The image labeling method based on characteristic scene of the present invention is described in more detail:

[0021] In step 1, an image segmentation algorithm is used to segment the labeled image used for learning to obtain a visual description of the image area.

[0022] Step 2, perform automatic semantic scene clustering on the labeled images used for learning. The specific method is as follows.

[0023] In the set of labeled images used for learning, high-density regions are selected as semantic scene clustering centers. In the present invention, the method of Shared Nearest Neighbor (SNN) is used to first construct a sample similarity matrix, and the nearest neighbor of each sample can adopt the intersection of its visual neighbor and semantically marked neighbor. Then, the sparse processing of k nearest neighbors is performed, and the nearest neighbor graph is constructed from this. By calculating the link strength of all sample points...

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Abstract

The invention provides an image marking method based on a characteristic scene, which comprises the steps of: segmenting a marked image used for learning by adopting an image segmenting algorithm, and obtaining vision description of an image region; 2, carrying out automatic semantic scene clustering on the marked image used for learning; 3, generating a characteristic scene space for each scene semantic category; 4, establishing corresponding semantic tree for each characteristic scene space; and 5, projecting an image to be marked in each characteristic scene space, determining the semanticcategory of the image to be marked for the fitting degree of a mixing model by adopting the projected vision characteristic and obtaining the final marking of the image through the semantic tree for the image for determining the semantic content. The image marking method fully utilizes the marked character information of a learning image, is used for carrying out automatic semantic scene clustering on the marked image used for learning, and ensures that more complete vision description is obtained under the special scene, thereby improving the reliability of automatic semantic marking throughthe image vision characteristic.

Description

technical field [0001] The invention relates to an automatic image labeling method. Background technique [0002] Image annotation is a challenging task, which has important implications for both image analysis understanding and image retrieval. Through the learning of the labeled image set, the relationship model between the semantic concept space and the visual feature space is established, and the unlabeled image set is labeled with this model. Due to the intricate correspondence between low-level and high-level semantics, the accuracy of automatic annotation is low. Under the condition of scene constraints, the mapping relationship between annotations and visual features can be simplified, and the reliability of automatic annotation can be improved. [0003] For scene classification of learned images, relying only on the visual features of the images obviously cannot guarantee the consistency of semantic content. As a very valuable resource, the labeled words of the i...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F17/30
Inventor 刘咏梅
Owner HARBIN ENG UNIV
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