Hazardous article three-dimensional image detection method and device, computer equipment and storage medium

Abstract

The invention discloses a hazardous article three-dimensional image detection method and device, computer equipment and a storage medium, and the hazardous article three-dimensional image detection method comprises the steps: receiving a hazardous article detection instruction, and obtaining a to-be-detected three-dimensional image, wherein the to-be-detected three-dimensional image is a reconstructed three-dimensional image after the to-be-detected object is scanned by security inspection equipment; performing 3D image segmentation on the to-be-detected three-dimensional image to obtain a plurality of square images; scanning and standardizing the target areas of all the block images to obtain a target area image; extracting hazardous article features in the target area image through a hazardous article detection model, and generating a feature vector graph; and obtaining an identification result output by the hazardous article detection model in a classified manner according to a K-means clustering algorithm. According to the hazardous article three-dimensional image detection method, segmentation, scanning and standardization processing are carried out on the three-dimensional image, and then classification and identification are carried out according to the K-means clustering algorithm, so that hazardous articles can be identified accurately, rapidly and automatically, and the satisfaction degree of customers is improved.

Description

technical field [0001] The invention relates to the field of image detection, in particular to a method, device, computer equipment and storage medium for detecting a three-dimensional image of dangerous goods. Background technique [0002] At present, places where security inspections are required, such as airports, stations, government agencies, subways, and prisons, are mostly equipped with X-ray security inspection machines, which image luggage items through X-rays, and then inspectors observe the X-ray images of luggage displayed on the monitor. X-ray images can be used to quickly determine whether there are dangerous goods in the luggage; in the process of luggage inspection, since the X-ray images are images that can be easily identified by abnormal visual inspection, the inspectors need to rely on the images observed by human eyes, and then rely on the inspectors Familiarity with image features such as the shape and color of dangerous goods and accumulated rich exper...

AI Technical Summary

Problems solved by technology

[0002] At present, places where security inspections are required, such as airports, stations, government agencies, subways, and prisons, are mostly equipped with X-ray security inspection machines, which image luggage items through X-rays, and then inspectors observe the X-ray images of luggage displayed on the monitor. X-ray images can be used to quickly determine whether there are dangerous goods in the luggage; in the process of luggage inspection, since the X-ray images are images that can be easily identified by abnormal visual inspection, the inspectors need to rely on the images observed by human eyes, and then rely on the inspectors Familiarity with image features such as the shape and color of dangerous goods and accumulated rich experience can quickly and accurately identify X-ray images of luggage, minimize the number of unpacking inspections, ensure rapid passage of personnel, and During the luggage inspection process, the inspectors need to concentrate on safety inspection for a long time, and the workload is huge; therefore, this solution has high requirements for the inspectors, and there are cases of manual judgment errors, and the inspectors are vulnerable to various external factors influence, it is difficult to guarantee accuracy

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