Dog Noseprint Recognition via Regional Image Segmentation
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Solution Overview
Problem
Existing dog identity recognition methods are plagued by low feasibility and significant harm to dogs, with current solutions like dog certificates having low penetration rates and microchipping being invasive and limited in recognition.
Innovation Solution
A dog nose print recognition method and system that involves collecting a nose image, processing it to obtain regional images, detecting key points for alignment, and extracting and recognizing dog nose print feature vectors to determine identity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the entire nose image is used for recognition, then the recognition accuracy may be improved, but the data processing time increases and response speed decreases
Solution Approach 1:
The patent divides the nose image into multiple regional images (first regional image, second regional image, third regional image, etc.) based on key anatomical landmarks such as nostril contours and nose bridge positions. This segmentation allows the system to process only relevant regions rather than the entire nose image, reducing computational load and processing time while maintaining recognition accuracy through focused analysis of discriminative features.
2Reliability
If more data is collected for detection, then the recognition completeness may be improved, but the processing complexity and time increase
Solution Approach 1:
The patent extracts and extracts only the necessary regional images that contain discriminative nose print features for identification. By selecting specific regions (such as nostril areas, nose bridge, and contour regions) rather than processing all available nose image data, the system reduces processing complexity while ensuring recognition completeness through focused analysis of key identification features.
3Ease of manufacture
If traditional dog identification methods like certificates or chips are used, then the implementation is simple, but the penetration rate is low or the method causes harm to the dog
Solution Approach 1:
The patent replaces traditional mechanical identification methods (physical certificates or implanted chips) with an optical/image-based recognition system. This substitution uses nose print pattern recognition through image processing and feature extraction, eliminating the need for physical tags or implants while achieving high penetration rates through contactless, rapid identification that can be performed with simple imaging devices.
4Productivity
If the nose image is divided into multiple regions, then the processing efficiency is improved, but the method complexity increases
Solution Approach 1:
The patent performs preliminary key point detection to identify anatomical landmarks (nostril contours, nose bridge positions, etc.) before dividing the nose image into regions. This preliminary action establishes a structured framework that guides the subsequent region division process, making the overall method more systematic and manageable despite the increased processing efficiency gains from regional analysis.
Data Source
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AI summary
The present disclosure provides a dog nose print recognition method and system. The dog nose print recognition method includes: collecting a nose image of a dog, acquiring the nose image, and processing the nose image to obtain a plurality of regional images to be recognized; performing key point detection on the plurality of regional images to be recognized to obtain key points corresponding to the regional images to be recognized, and using the key points to perform alignment processing of the regional images to be recognized to obtain aligned regional images to be recognized; and performing dog nose print feature vector extraction and recognition on the aligned regional images to be recognized, and determining a dog identity recognition result through the dog nose print feature vector extraction and recognition. The system includes modules corresponding to the steps of the method.