Vision System for Animal Identification Using 3D and 2D Imaging
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional animal identification methods face challenges such as unintentional damage or tampering of electronic tags, and difficulties in cow face recognition due to varying perspectives, leading to inefficient and unreliable identification processes.
Innovation Solution
A vision system combining three-dimensional or thermographic images for body part detection and two-dimensional images for identification, using control circuitry to align and correlate images for efficient and robust animal identification without the need for RFID tags or other markings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If electronic identification methods (RFID tags, microchips) are used for animal identification, then identification can be performed without invasive procedures, but the system becomes vulnerable to unintentional damage, intentional tampering, or unavailability of scanning devices
Solution Approach 1:
The patent replaces electronic identification systems (RFID tags, microchips, scanners) with a vision-based identification system using cameras and image processing. This substitution eliminates the need for electronic components that can be damaged or tampered with, while maintaining non-invasive identification. The system captures images of animals and uses computer vision algorithms to identify individuals based on visual features.
2Ease of operation
If face recognition software is used for cow identification, then biometric identification without invasive procedures is achieved, but the system fails when cows approach the camera from very different perspectives
Solution Approach 1:
The patent transitions from traditional 2D face recognition to 3D imaging for animal identification. By capturing three-dimensional images or thermographic images, the system can recognize animals from various perspectives and orientations. The 3D depth information provides robustness against changes in viewing angle, allowing reliable identification regardless of the animal's approach direction to the camera.
Solution Approach 2:
The patent employs thermographic imaging as an alternative parameter for capture. Thermal images provide different contrast and feature information compared to visible light images, enabling body part detection even when the animal's orientation varies. This parameter change enhances the system's ability to handle diverse perspectives.
3Device complexity
If a single image type is used for both body part detection and identification, then the system is simpler, but it cannot achieve both fast robust detection and reliable identification simultaneously
Solution Approach 1:
The patent divides the identification process into two distinct stages using different image types: first, body part detection using 3D or thermographic images for fast and robust localization; second, identification using 2D images for accurate recognition. This segmentation allows each stage to use the most suitable image modality, achieving both speed in detection and accuracy in identification while maintaining manageable system complexity through modular processing.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables fast and reliable animal identification by leveraging the strengths of different image types for body part detection and identification, improving efficiency and reliability in applications like milking and feeding management.
Implementation Method 1
The first image sensor arrangement is configured to capture three-dimensional or thermographic images of the individual animal
Implementation Method 2
The second image sensor arrangement is configured to capture two-dimensional images of the individual animal
Data Source
AI summary
A vision system for determining an identity of an individual animal in a population of animals with known identity is provided. A first image sensor arrangement is configured to capture three-dimensional or thermographic images of the individual animal. A second image sensor arrangement is configured to capture two-dimensional images of the individual animal. Control circuitry is configured to obtain a first image of the individual animal captured by the first image sensor arrangement and to detect a body part in the first image, and in response to detecting the body part, obtain a second image of the individual animal captured using the second image sensor arrangement, and to identify the individual animal by comparing metrics of the second image with the reference data in a data storage.