Method for extracting significant object based on region significance

Abstract

The invention discloses a method for extracting a significant object based on region significance. The method comprises the following steps: firstly, establishing a significant image with constant scaThe invention discloses a method for extracting a significant object based on region significance. The method comprises the following steps: firstly, establishing a significant image with constant scale through by calculating the multiresolution contrast feature of an input image, and dividing the input image into different regions by a non-parameter nuclear density evaluation method; secondly, anle through by calculating the multiresolution contrast feature of an input image, and dividing the input image into different regions by a non-parameter nuclear density evaluation method; secondly, and then, calculating specific values of region significance of each region assembly and a complementary set thereof; and finally, extracting the significant object through by acquiring the maximum valud then, calculating specific values of region significance of each region assembly and a complementary set thereof; and finally, extracting the significant object through by acquiring the maximum value in the specific values, which comprises the following steps: (1) inputting the an image, and establishing the a significant image with constant scale; (2) inputting the image to realize image segmene in the specific values, which comprises the following steps: (1) inputting the an image, and establishing the a significant image with constant scale; (2) inputting the image to realize image segmentation; and (3) extracting the significant image. The method is combined with the region significance, not only can accurately extract a single significant object, but also can extract a plurality oftation; and (3) extracting the significant image. The method is combined with the region significance, not only can accurately extract a single significant object, but also can extract a plurality ofsignificant objects, so that the extracted significant object can meet the requirement of human vision, and can improve the accuracy of segmentation.significant objects, so that the extracted significant object can meet the requirement of human vision, and can improve the accuracy of segmentation.

Description

technical field [0001] The invention relates to a computer image processing method, in particular to an image segmentation method. Background technique [0002] Image segmentation is an important issue in the fields of image analysis, pattern recognition and computer vision, and it is also a difficult issue. The ultimate goal of image segmentation is to segment objects with specific practical significance, that is, semantic objects. Some methods use recognizable high-level information (such as faces and text) and image saliency to locate salient objects in images. However, its use is limited because some images do not have identifiable high-level information, or even if identifiable high-level information exists, it is difficult to automatically extract it. Image saliency is always available, but it does not provide enough information for locating salient objects in an image. Low-level spatial features do not necessarily match salient objects well. For example, some high-...

AI Technical Summary

Problems solved by technology

Furthermore, existing image saliency detection methods cannot identify salient image features that appear at different image scales

If the saliency problem of invariant image scale is not solved, the salient features on some image scales will be lost, resulting in unsatisfactory image segmentation results.

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