Improved YOLOv8 Detection Algorithm in Security Inspection Image

TL;DR

This paper introduces an improved YOLOv8-based algorithm, CSS-YOLO, tailored for security inspection X-ray images to address issues like object overlap, false positives, and missed detections.

Contribution

The paper proposes a novel CSS-YOLO algorithm that enhances YOLOv8s for more accurate X-ray contraband detection in security inspections.

Findings

Improved detection accuracy in X-ray security images

Reduced false detection and missed detections

Enhanced handling of overlapping objects

Abstract

Security inspection is the first line of defense to ensure the safety of people's lives and property, and intelligent security inspection is an inevitable trend in the future development of the security inspection industry. Aiming at the problems of overlapping detection objects, false detection of contraband, and missed detection in the process of X-ray image detection, an improved X-ray contraband detection algorithm CSS-YOLO based on YOLOv8s is proposed.