Golf Ball Detection Using Dynamic Segmentation and Polar Coordinate Correction
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Solution Overview
Problem
Current golf systems face challenges in positioning accuracy due to environmental adaptation issues when processing images from image sensors, leading to reduced precision in detecting golf ball movement.
Innovation Solution
The method involves correcting camera distortion using polar coordinate transformation, calibrating the camera, and employing dynamic segmentation based on fuzzy entropy and gradient-based methods to improve image processing and extract accurate coordinate data and rotating speed of the golf ball.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If environmental adaptation is not applied when processing images from the image sensor, then the processing procedure is simpler, but the positioning accuracy is reduced
Solution Approach 1:
The patent applies parameter changes by dynamically adjusting image processing parameters based on ambient light conditions. The system detects light intensity and modifies segmentation thresholds, brightness normalization factors, and contrast enhancement parameters accordingly. This allows the processing procedure to adapt to environmental changes while maintaining positioning accuracy without requiring complete procedural redesign.
Solution Approach 2:
The patent implements dynamics by making the image processing procedure adaptive rather than static. The system continuously monitors ambient light conditions and dynamically adjusts processing parameters in real-time. The segmentation algorithm, brightness correction, and contrast enhancement are all made dynamic, allowing the system to respond to changing environmental conditions while maintaining accurate positioning.
2Measurement precision
If dynamic segmentation based on fuzzy entropy is used, then the positioning accuracy is improved, but the processing time increases
Solution Approach 1:
The patent applies preliminary action by performing pre-processing steps such as brightness normalization and contrast enhancement before the main segmentation process. These preliminary actions prepare the image data in advance, reducing the computational burden during the actual segmentation phase. The system pre-calculates adjustment factors and prepares lookup tables that speed up the fuzzy entropy segmentation process.
Solution Approach 2:
The patent implements segmentation by dividing the image processing into distinct phases: pre-processing (brightness/contrast adjustment), segmentation (fuzzy entropy-based separation), and post-processing (position calculation). This segmentation allows each phase to be optimized independently, with the segmentation phase focusing purely on separation while pre-processing handles data preparation, thereby reducing overall processing time while maintaining accuracy.
3Measurement precision
If gradient-based dynamic segmentation is applied, then the extraction of mark information is improved, but the computational complexity increases
Solution Approach 1:
The patent applies local quality by computing gradients and performing segmentation operations only in specific regions of interest rather than the entire image. The system identifies the golf ball region through preliminary detection and applies the computationally intensive gradient-based segmentation only to that local area. This significantly reduces the computational complexity while maintaining high mark extraction accuracy in the critical region.
Data Source
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AI summary
The present application discloses a floor-type golf ball detection method, a system, and a storage medium. The method includes the following steps: correcting distortion of the camera; calibrating a camera; triggering of hitting a ball: monitoring a pixel variation value of a serving position of a golf ball in a picture captured by the camera in real time, and determining triggering of hitting a ball when the pixel variation value of the position exceeds a threshold value; positioning a golf ball: processing the picture captured by the camera after triggering of hitting a ball with a dynamic segmentation based on a fuzzy entropy, and positioning the processed picture to acquire coordinate data of the golf ball; calculating parameters; and detecting a rotating speed of the golf ball: extracting a mark on the golf ball in the picture used for positioning by performing a gradient-based dynamic segmentation method, and acquiring the rotating speed based on angular variation of the extracted mark in the picture. The present application improves the positioning accuracy of the golf system in the positioning processing.