Pet Identification via Phenotype Image Analysis
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Solution Overview
Problem
Current pet recovery services face challenges in identifying and reuniting lost pets without identification tags or microchips, as they rely heavily on physical identifiers that may not be readily available or accurate.
Innovation Solution
A domestic animal identification service using a graphical user interface that analyzes images of pets to extract phenotypes and match them with profiles in a database, dynamically updating search results based on user-input parameters and image analysis to improve accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If physical identifiers like collar tags or microchips are used for pet identification, then identification reliability is improved, but device complexity and ease of operation worsen because not all pets have these identifiers and the process becomes more complex when they are missing
Solution Approach 1:
The system creates a digital copy of the pet's visual appearance through image analysis and phenotype extraction. Instead of relying on physical tags or microchips, the system generates a digital phenotype profile from images that can be compared against registered pet profiles, providing a non-invasive alternative identification method.
Solution Approach 2:
The patent replaces mechanical/physical identification systems (collar tags, microchips) with an optical/image-based system. The phenotype extraction tool analyzes visual features from images to create identification profiles, substituting the need for physical identifiers with a visual recognition approach.
2Measurement precision
If phenotype extraction from images is implemented, then measurement precision of pet characteristics is improved, but device complexity increases due to the need for image analysis tools and processing systems
Solution Approach 1:
The system performs self-service by automatically extracting phenotypes from images without requiring manual measurement or input from users. The phenotype extraction tool autonomously analyzes image data to identify and record pet characteristics, eliminating the need for human observers to manually assess and input physical traits.
Solution Approach 2:
The system performs preliminary action by pre-extracting and storing phenotype data from images before the actual identification process. When a pet needs identification, the system has already processed reference images and created phenotype profiles, enabling rapid comparison and matching without performing complex analysis at the moment of identification.
3Productivity
If dynamic updating of profile display region is implemented, then productivity of pet identification process is improved, but device complexity increases due to real-time filtering and sorting requirements
Solution Approach 1:
The system applies partial action by initially displaying a subset of matching profiles based on primary criteria (species, basic phenotype), then progressively filtering and refining results as users provide additional parameters or interact with the interface. This staged approach improves productivity by showing relevant results quickly while maintaining the option to refine searches.
Solution Approach 2:
The profile display region dynamically adapts its content and organization based on user interactions and input parameters. The system adjusts the displayed profiles in real-time, reordering and filtering results as users refine their search criteria, creating a flexible and responsive identification process that optimizes productivity.
Data Source
AI summary
Technologies are described for a domestic animal identification service. In one example, domestic animal profiles can be dynamically displayed in a profile display region of a graphical user interface. Domestic animal profiles that correspond to one or more phenotypes can be obtained from a profile data store, and the domestic animal profiles can be displayed in a profile display region of the graphical user interface to allow user-identification of a profile that may be associated with the domestic animal. The profile display region of the graphical user interface can be dynamically updated to include domestic animal profiles that correspond to identification parameters input to the graphic user interface.