An Automatic Forensic Injury Annotation Method and System Based on Image Segmentation Technology

By using an automatic injury labeling method based on image segmentation technology, the automatic labeling device captures video images of wounds and predicts the best shooting angle, solving the problem of low efficiency in manually filling in injury results by forensic doctors, and realizing rapid and accurate injury level assessment and labeling.

CN118840365BActive Publication Date: 2025-11-14ZHEJIANG FEITU IMAGING TECH CO LTD
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Patent Information

Application Number
CN202411127919.7
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2024-08-16
Publication Date
2025-11-14
Estimated Expiration
2044-08-16

AI Technical Summary

Technical Problem

The current method of injury investigation requires forensic doctors to manually fill in the results, which is inefficient and cannot meet the actual needs.

Method used

An automatic injury labeling method for forensic injury identification based on image segmentation technology is adopted. Video images of the wound area are captured by an automatic labeling device, the external shape data of the wound is extracted using image segmentation technology, and the target display posture is predicted by combining the posture prediction model to determine the best shooting angle. The injury level is then automatically labeled in the high-definition image.

Benefits of technology

It enables rapid and automatic assessment and labeling of injury severity, greatly reducing the workload of forensic doctors, improving the efficiency of injury identification, and ensuring the accuracy of injury severity rating.

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Abstract

This invention belongs to the field of forensic identification technology. It provides a method and system for automatic annotation of forensic injuries based on image segmentation technology. The method includes: an automatic annotation device capturing video images of the wound area targeted in the forensic examination; using image segmentation technology to extract the external shape data of the wound from the video images; a posture prediction model analyzing and processing the external shape data to predict the target's display posture; determining the target shooting angle based on the target's display posture; while the forensic examiner displays the wound area of ​​the target object, the automatic annotation device capturing high-definition images of the displayed wound area according to the target shooting angle; extracting wound feature data from the high-definition images; assessing the injury severity level of the wound area based on the wound feature data; automatically annotating the injury severity level in the high-definition images; and saving the data. This method enables automatic assessment of wound severity levels and automatic annotation in high-definition images, improving the efficiency of forensic injury examination.
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