Adaptive Fingerprint Image Preprocessing for Multi-Sensor Recognition
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Solution Overview
Problem
Current fingerprint recognition technologies face challenges in handling images from sensors of varying specifications, leading to inconveniences such as inaccurate fingerprint input and recognition issues due to differences in sensor size and quality, which can result in non-fingerprint areas being included in images, affecting recognition rates and authentication performance.
Innovation Solution
An image preprocessing method that involves obtaining an input image, setting edge lines, calculating energy values, and adaptively cropping the image based on these values to remove non-fingerprint areas and adjust the image size to a power of 2, enhancing the image using frequency transforms, and determining effective areas for improved recognition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If image preprocessing is performed on images from sensors of various specifications, then recognition accuracy is improved, but processing complexity increases
Solution Approach 1:
The patent applies parameter changes by dynamically adjusting image processing parameters based on sensor specifications. The system detects sensor characteristics and modifies preprocessing parameters accordingly, transforming a complex multi-sensor processing problem into a manageable adaptive process that maintains recognition accuracy while controlling complexity
Solution Approach 2:
The patent implements dynamics through adaptive image preprocessing that dynamically adjusts to different sensor specifications. The system continuously adapts processing parameters based on detected sensor characteristics, enabling flexible handling of various sensor types without requiring fixed complex processing pipelines for each sensor variant
2Reliability
If the entire input image is processed, then all potential fingerprint areas are captured, but processing time increases
Solution Approach 1:
The patent applies the extraction principle by isolating and processing only the effective fingerprint areas within the input image. The system identifies and extracts regions containing fingerprint information, excluding non-fingerprint areas from processing. This selective approach maintains complete fingerprint capture while significantly reducing the amount of data requiring processing, thereby decreasing processing time
Solution Approach 2:
The patent implements segmentation by dividing the input image into effective and non-effective areas. The system segments the image based on fingerprint presence detection, creating separate processing regions. This segmentation allows the system to focus computational resources only on relevant fingerprint-containing regions, improving processing efficiency while maintaining recognition reliability
3Measurement precision
If non-fingerprint areas are removed from the image, then recognition rate is improved, but image processing complexity increases
Solution Approach 1:
The patent applies preliminary action by performing non-fingerprint area removal as a preprocessing step before main recognition processing. The system proactively identifies and eliminates non-fingerprint regions in advance, ensuring that subsequent recognition operations work only with relevant data. This preliminary filtering simplifies the overall processing pipeline by preventing unnecessary complexity in later recognition stages
Data Source
AI summary
A method of preprocessing an image including biological information is disclosed, in which an image preprocessor may set an edge line in an input image including biological information, calculate an energy value corresponding to the edge line, and adaptively crop the input image based on the energy value.