Visual attention mechanism-based method for detecting target in nuclear environment

Abstract

The invention discloses a visual attention mechanism-based method for detecting a target in a nuclear environment. The method includes: extracting brightness, color, direction features collected by an ordinary camera, and so as to obtain three feature saliency images; performing weighing fusion on the abovementioned saliency images to obtain a weighting saliency image; obtaining regions of interest according to the weighing saliency image and performing feature extraction on the region of interests; extracting features of a gamma camera mixed graph; and using an SIFT method to fuse the regions of interest with the mixed graph, and detecting the position of the target. The visual attention mechanism-based method for detecting the target in the nuclear environment uses a bottom-up data drive attention model to extract the plurality of regions of interests, and greatly reduces the calculated amount of a later matching process; then combines the plurality of regions of interest with the up-down task drive attention model to establish a bidirectional visual attention model, detection precision and processing efficiency of target areas in the images can be greatly improved, and a matching process eliminates interference of unrelated regions in a scene, thereby enabling extracted operation target to have better robustness and accuracy.

Description

technical field [0001] The invention relates to the technical field of image information processing, in particular to a method for detecting objects in a nuclear environment based on a visual attention mechanism. The method specifically adopts a top-down and bottom-up bidirectional visual attention model, which can be used in special environments target detection. Background technique [0002] With the rapid development of information technology and the expansion of data, people have higher and higher requirements for the speed and accuracy of information processing. The ideal information processing process is that only part of the information related to the task needs to be processed, but the actual information processing process needs to process a lot of information that is not related to the task. Therefore, how to quickly find and process only the part of the information related to the task becomes very important. [0003] The human visual attention mechanism provides ...

AI Technical Summary

Problems solved by technology

This method first needs to assume that the image has been divided into several physically meaningful objects or combinations of objects, so manual intervention is required

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