Saliency detecting element evaluation method based on image retrieval

Abstract

The invention discloses a saliency detecting element evaluation method based on image retrieval. The method comprises the following steps: respectively taking a saliency map labeled by a user and a saliency map generated by T saliency detection algorithms to serve as a weighted color histogram of a weight calculation input image, and acquiring a retrieval image by utilizing an image retrieval method based on the content so as to respectively obtain the retrieval sequences L and Lk; respectively calculating similarity values of the retrieval sequences L and Lk, and sorting to obtain an evaluated sorting sequence X of the image retrieval application on the T saliency detection algorithms; respectively calculating evaluation values of the saliency detection evaluation method on the T saliency detection algorithms, and sorting to obtain an evaluated sorting sequence Xb of the saliency detection evaluation method on the T saliency detection algorithms; calculating the correlation between the sequences X and Xb; and taking the average value of the correlations of all input images in an image set as the evaluated value of the saliency detection evaluation method. The method disclosed by the invention contributes to selecting a proper and effective saliency detection evaluation method for the actual application.

Description

technical field [0001] The invention relates to the technical fields of image and video processing and computer vision, in particular to an image retrieval-based salient detection element evaluation method. Background technique [0002] Saliency detection is used to extract salient regions in an image. Since saliency detection can be used as an image preprocessing step to reduce the computational complexity of problems in the field of computer vision, saliency detection has always been a research hotspot in the field of computer vision. Many saliency detection algorithms have been proposed for various practical applications, such as object recognition, image retrieval, image compression, etc. Different saliency detection algorithms have different performances, resulting in different effects obtained by using different saliency detection algorithms in practical applications. Therefore, the saliency detection evaluation method for selecting an appropriate saliency detection a...

AI Technical Summary

Problems solved by technology

First, different saliency detection evaluation methods often have inconsistent evaluation results for the same saliency detection algorithm

Secondly, most of the saliency detection evaluation methods evaluate the image saliency detection algorithm from the theory, and lack the evaluation of the saliency detection algorithm from the perspective of practical application.

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