Biological Image Processing Device Rotation Correction
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Solution Overview
Problem
Current biological image processing methods increase authentication accuracy by setting smaller rotation angles, but this results in higher computational costs due to the need to check a larger number of images.
Innovation Solution
A biometric authentication device and method that calculates local orientations of biological curves using differential filters or Gabor filters, allowing for precise rotation angle correction at a lower computational cost by turning filter responses into vectors and combining them, thereby achieving high authentication accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If rotation angles are set at smaller intervals to increase authentication accuracy, then authentication accuracy is improved, but computational costs increase due to checking a larger number of images
Solution Approach 1:
The patent applies preliminary action by calculating local orientations of biological curves in advance using differential filters or Gabor filters. This pre-computed orientation information is then used to determine the optimal rotation angle directly, eliminating the need to check multiple rotated images at small angle intervals. The preliminary extraction of orientation features enables accurate rotation correction with minimal computational effort.
Solution Approach 2:
The patent extracts the essential orientation information from biological curves using filter responses that are converted into vectors. By taking out only the relevant orientation components and combining them through vector operations, the system identifies the optimal rotation angle without needing to process all possible rotation angles, thus reducing computational cost while maintaining authentication accuracy.
2Manufacturing precision
If multiple rotated images are checked to correct yaw rotation shifts, then positional shift correction is improved, but processing time increases
Solution Approach 1:
The patent replaces the mechanical approach of physically rotating and checking multiple images with a mathematical substitution. By using differential filters or Gabor filters to calculate local orientations and determining the optimal rotation angle through vector operations, the system directly computes the correction needed without iteratively processing multiple rotated versions of the image, significantly reducing processing time.
Solution Approach 2:
The patent performs preliminary calculation of local orientations along biological curves before the actual rotation correction is applied. This pre-computed orientation data enables direct determination of the optimal rotation angle, eliminating the time-consuming process of checking multiple rotated images while ensuring accurate positional shift correction.
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
The method enables high authentication accuracy with reduced computational costs by accurately calculating rotation angles and absorbing noise, ensuring robust correction and efficient processing.
Implementation Method 1
A biometric authentication device and method that calculates local orientations of biological curves using differential filters or Gabor filters
Implementation Method 2
A biometric authentication device and method that calculates local orientations of biological curves using differential filters or Gabor filters
Data Source
Figure 1A~1B
Figure 2
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AI summary
A biological image processing device includes: a line extracting unit configured to extract at least one line from contours of a palm and principal lines of the palm shown in an image of the palm; a pixel extracting unit configured to extract pixels of the line extracted by the line extracting unit; a local region setting unit configured to set a local region for each of the pixels, each local region including each corresponding one of the pixels; a local orientation calculating unit configured to calculate, for each local region, local orientations of the line extracted by the line extracting unit, in accordance with gradient intensities related to respective orientations of each corresponding local region; and an orientation calculating unit configured to calculate an orientation of the palm in accordance with a statistical amount of the respective local orientations.