Machine-Vision Golf Ball Sorting for High-Speed Classification
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Solution Overview
Problem
Existing golf ball sorting systems are labor-intensive, prone to errors, and inefficient, particularly when handling large volumes, and lack the ability to accurately identify and sort golf balls based on multiple parameters.
Innovation Solution
An automated golf ball sorting system with a hopper conveyor assembly, control system, and sorter assembly that uses image recognition technology to classify and categorize golf balls by size, weight, brand, and condition, capable of processing up to one ball per second with over 90% accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual sorting is used, then flexibility in handling various ball types is maintained, but labor intensity and time consumption increase significantly
Solution Approach 1:
The patent replaces manual mechanical sorting with an automated system using image recognition technology. A camera captures images of golf balls on a conveyor, and a processing system analyzes brand logos, ball types, and conditions to automatically control sorting gates, eliminating the need for manual inspection while maintaining high-speed operation capability
Solution Approach 2:
The system enables self-service sorting where the golf balls themselves provide identification information through their visible markings and features. The image recognition system automatically detects brand logos, ball types, and defect conditions without requiring external tagging or identification mechanisms, allowing the balls to 'identify themselves' during transit
2Device complexity
If simple mechanical sorting is used, then device complexity is reduced, but measurement precision for identifying ball characteristics deteriorates
Solution Approach 1:
The patent replaces complex mechanical measurement and identification mechanisms with an optical image recognition system. Instead of using mechanical probes or sensors to measure ball characteristics, the system uses a camera to capture images and software algorithms to identify brand logos, ball types, and defects, achieving high precision with simpler hardware
Solution Approach 2:
The system creates optical copies (images) of the golf balls during conveyor transit and performs all identification and classification operations on these digital copies rather than requiring physical manipulation or contact measurement of the actual balls. This allows multiple parameters to be measured simultaneously from a single image capture
3Extent of automation
If prior art sorting machines are used, then automation is achieved, but reliability and sorting accuracy deteriorate due to complexity
Solution Approach 1:
The patent replaces unreliable complex mechanical sorting mechanisms with a robust optical recognition and control system. The image recognition technology provides consistent and reliable identification of ball characteristics, while the electronic control system accurately actuates sorting gates based on digital decisions, eliminating mechanical wear and alignment issues
Solution Approach 2:
The system implements real-time feedback control where the image recognition system continuously monitors golf balls on the conveyor, identifies their characteristics, and immediately adjusts sorting gate positions based on the analyzed data. This closed-loop control ensures high sorting accuracy and allows for real-time correction of any identification or actuation errors
4Productivity
If high-speed sorting is implemented, then productivity increases, but measurement precision for detecting ball conditions deteriorates
Solution Approach 1:
The system performs preliminary action by capturing images of all golf balls during their natural transit on the conveyor before sorting decisions are made. This allows the image recognition system to analyze multiple ball characteristics simultaneously and prepare sorting commands in advance, maintaining high-speed operation without compromising detection accuracy
Solution Approach 2:
The system creates digital copies (images) of the golf balls at high speed during conveyor transit and performs all defect detection and classification operations on these copies. This allows for thorough analysis of ball conditions including scratches, dirt, and branding without requiring physical contact or slowing down the ball flow
Data Source
AI summary
An automated golf ball sorting apparatus and method of use is provided. A machine vision system and neural network classification sort golf balls by brand, model, or condition. The system includes a chain-driven elevator with inclined ball platforms that rotate each ball in two planes along a high-friction roller. A camera captures images of each rotating ball, which are classified using a trained convolutional neural network. A microcontroller tracks each ball's progress using infrared sensor interrupts and dynamically assigns it to a solenoid-actuated gate for diversion into a corresponding sort bin. A user loads mixed balls into a hopper; the system lifts, scans, classifies, and sorts them in real time, processing one ball per second with over 90% accuracy. A training mode enables collection of annotated image data using single-type ball loads to refine the neural network.