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Image importance detection method based on photographic element

A detection method and an important technology, which is applied in the field of image processing, can solve problems such as not many, who have not studied the thinking of the photo shooter, and achieve the effect of fast classification speed, high classification accuracy rate, and wide application prospects

Inactive Publication Date: 2012-07-18
ZHEJIANG UNIV
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  • Claims
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Problems solved by technology

However, there are not many methods for calculating the importance of images, especially the method of using photographic elements to reflect the thinking of the photographer.

Method used

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  • Image importance detection method based on photographic element
  • Image importance detection method based on photographic element
  • Image importance detection method based on photographic element

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Embodiment Construction

[0018] First define the abbreviations to be used in the following description: Depth of Field (Depth of Field) is abbreviated as DOF, and Gaussian deviation edge detection method (Difference of Gaussian) is abbreviated as DOG.

[0019] figure 1 It is the basic flow chart of the present invention. The present invention uses images as input and does not require any user interaction to obtain an importance map reflecting the importance of each region on the image. The following describes each process of the present invention in detail:

[0020] 1. Color analysis

[0021] Color can affect people's visual attention. In the past, most of the research on the importance of color focused on the calculation of color contrast, and few studies focused on the importance difference between colors. In fact, photographers often use bright colors (such as red) to attract attention.

[0022] We base the color sensitivity model on the HSV color space. First, we determined the color importance ...

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Abstract

The invention discloses an image importance detection method based on a photographic element, which comprises the following steps: (1) color analysis; (2) depth-of-field analysis; (3) structure analysis; and finally, outputting an importance diagram for reflecting the attention degree of each pixel of an image. The image importance detection method has the benefits that firstly, a method for reflecting the understanding to a scene when a photographer shoots the scene is provided, and through the method, the defect that a shallow depth-of-field image can not be processed through the existing importance diagram detection method can be effectively overcome; secondly, compared with the existing method, an provided image depth-of-field classification method has the advantages of high classification accuracy and quick classification speed; thirdly, the image importance detection method has wide application prospect and can be applied to the image retrieval based on contents, the automatic segmentation of image objects and the field of automatic monitoring and tracking of video objects and the like.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to an image importance detection method based on photographic elements. Background technique [0002] The image importance detection method based on photographic elements belongs to the field of computer vision and cognition. Image importance detection has broad application prospects. For example, it can be used in content-based image retrieval, which can improve the accuracy of its retrieval and reduce the amount of calculation; When used as an input, automatic image segmentation of image objects can be performed; similarly, it can also be applied to the field of video surveillance for automatic tracking of objects, etc. However, there are not many research methods for calculating the importance of images at present, especially there is no research on the method of using photographic elements to reflect the thinking of the photographer. Contents of the invention [0003...

Claims

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Application Information

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IPC IPC(8): G06T7/40G06T7/60
Inventor 丛林童若锋
Owner ZHEJIANG UNIV
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