Automated Cartridge Case Base Segmentation Using Surface Height Matrix
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Solution Overview
Problem
Current methods for automatic matching of cartridge cases after firing are time-consuming and inefficient, requiring manual segmentation and comparison, which hinders rapid identification and increases the workload for experts in criminology.
Innovation Solution
A model-based method using surface height matrix information for segmentation, involving center detection, circle detection, and firing pin mark identification, along with letter and sign detection, to automate the process and enhance matching efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual segmentation and comparison of cartridge case regions is performed, then analysis accuracy is maintained, but time consumption increases and expert workload increases
Solution Approach 1:
The cartridge case base is divided into multiple regions of interest (primer region, ejector mark region, firing pin mark region) based on surface height matrix information. This segmentation allows automated processing of each region while maintaining the accuracy of forensic analysis, resolving the contradiction between manual analysis precision and time consumption.
Solution Approach 2:
The system automatically performs segmentation and comparison of cartridge case regions using algorithms that process surface height matrix data. The automated system serves itself by performing analysis tasks that would otherwise require expert manual intervention, thereby reducing time consumption while maintaining accuracy through consistent algorithmic processing.
2Loss of time
If automated segmentation system is implemented, then time consumption is reduced, but system complexity increases
Solution Approach 1:
Manual mechanical segmentation and visual comparison processes are replaced with automated computational algorithms that process surface height matrix information. This substitution reduces time consumption while managing system complexity through software-based solutions rather than complex hardware systems.
Solution Approach 2:
The system transforms 2D images into surface height matrix representations, changing the data parameters to enable automated segmentation. By representing the cartridge case base as a height field with measurable surface variations, the system simplifies the automated detection of regions and marks, managing complexity through data transformation rather than complex processing algorithms.
3Quantity of substance
If 2D or 3D information systems are used for data acquisition, then marking information can be captured, but accurate acquisition of marks becomes more difficult
Solution Approach 1:
The system transitions from 2D image data to 3D surface height matrix representations of the cartridge case base. This dimensional change enables automated detection and measurement of marks by analyzing surface height variations, thereby improving mark acquisition accuracy while capturing comprehensive marking information.
Solution Approach 2:
The surface height matrix serves as an intermediary representation that bridges the gap between raw 2D/3D data and the marks themselves. By transforming the cartridge case base into a height field representation, the system facilitates accurate mark detection and measurement, resolving the difficulty of directly acquiring mark information from raw data.
Data Source
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AI summary
One of the significant problems encountered in criminology studies is the successful automatic matching of cartridge cases after a cartridge is fired from a firearm, on the basis of the marks left on the cartridge cases fired. One of the probable steps in the solution of this problem is the segmentation of certain regions defined on the cartridge case. This invention relates to the method for segmentation of cartridge case base by using surface height matrix information.