Target Image Aberration Detection for Automated Shot Scoring
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Solution Overview
Problem
Existing target shooting systems require manual scoring and lack automated methods to identify shot locations on targets, limiting real-time scoring and remote competition capabilities.
Innovation Solution
An image acquisition system using a camera and processing device to analyze target images, employing image recognition techniques to automatically identify shot locations, and share scoring data across networks for real-time and historical tracking.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If manual scoring is used to identify shot locations on targets, then the system is simple to implement, but real-time scoring and remote competition capabilities are lost
Solution Approach 1:
The patent replaces manual mechanical scoring with an automated image processing system that uses computer vision algorithms to detect shot locations on targets. The system captures images of targets and automatically identifies shot positions through digital image analysis, eliminating the need for manual inspection and scoring while enabling real-time results.
Solution Approach 2:
The patent creates a digital copy of the target and shot locations through image capture and processing. Instead of physically examining the target, the system uses digital images and algorithms to replicate the scoring function, allowing remote viewing and automated analysis of shot positions without direct physical interaction with the target.
2Productivity
If automated image recognition is implemented to identify shots, then real-time scoring is enabled, but the system becomes dependent on image processing algorithms
Solution Approach 1:
The patent performs preliminary actions by capturing images of the target and pre-processing them before actual shot detection. The system prepares the image data, establishes reference frames, and sets up detection parameters in advance, which enables faster real-time processing when shots occur while maintaining detection accuracy through pre-established algorithms.
3Adaptability or versatility
If the system uses color-based shot identification, then it can work with various target colors, but it becomes sensitive to lighting conditions and color variations
Solution Approach 1:
The patent employs parameter changes by adjusting image processing parameters such as color thresholds, brightness levels, and contrast settings to adapt to different target colors and lighting conditions. The system dynamically modifies detection parameters based on the captured image characteristics, enabling consistent shot identification across varied target colors while compensating for environmental variations.
Data Source
AI summary
Aberrations on a surface, such as shots on a target, are identified through image processing techniques using color subtraction. An image of the surface is first initialized by shrinking the image and identifying pixel colors. A quantization algorithm is used to identify K number of colors, and acceptable variations for those colors are identified, and then stored in a color palette. Future images are analyzed by subtracting colors that match colors in the color palette. Remaining colors are aged in, and then compared with previously identified aberrations (shots). Image processing techniques then verify the potential aberrations. Data concerning verified aberrations are then displayed on remote user interfaces.