Image significance object detection method based on adaptation fusion mechanism

Abstract

The present invention discloses an image significance object detection method based on an adaptation fusion mechanism. Location detection of the significance area of an image is performed through color, depth and distance information, the initial detection result of a significance object in the image is obtained, and an adaptation fusion mechanism is employed to optimize a final result of significance detection. The image significance object detection method based on the adaptation fusion mechanism employs the multi-layered depth information to perform significance detection to increase accuracy of detection of the significance object; and the present invention further provides an adaptation fusion mechanism to increase the robustness of the significance detection through continuous fusion so as to apply to more complex scenes and widen the application range. The image significance object detection method based on the adaptation fusion mechanism can more accurately display the significance area in the image to provide accurate and useful information to the following applications such as target identification and classification, etc.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to a method for detecting salient objects in an image by using an adaptive fusion mechanism. Background technique [0002] When facing a complex scene, the human eye will quickly focus on a few prominent visual objects and give priority to these objects. This process is called visual saliency. Saliency detection uses the visual biological mechanism of the human eye to simulate the proper processing of the image by the human eye with mathematical calculation methods, so as to obtain the salient object of a picture. Since we can prioritize the allocation of computing resources required for image analysis and synthesis through salient regions, it is of great significance to detect salient regions of images through computation. The extracted saliency images can be widely used in many computer vision applications, including image segmentation of objects of interest, object dete...

AI Technical Summary

Problems solved by technology

[0006] The purpose of the present invention is to address the above-mentioned deficiencies in the prior art, and propose a new image salient object detection method based on an adaptive fusion mechanism, which can solve the problem that the existing salient detection is not accurate enough and not robust enough, so that The salient regions in the image are more accurately displayed, providing accurate and useful information for later applications such as target recognition and classification

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