Palm Print Image Segmentation and Core Line Extraction
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Solution Overview
Problem
Manual operation of region determination and core line extraction in palm print verification is impractical due to the larger size and greater data volume of palm print images compared to fingerprint images.
Innovation Solution
An image processing apparatus that divides a palm print image into multiple divisional images, uses a fingerprint model to determine valid regions and extract core lines in each divisional image, and integrates the processed images to generate a complete processed palm print image.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual region determination and core line extraction are performed on palm print images, then processing accuracy can be maintained, but the workload becomes impractical due to the large size and data volume of palm print images
Solution Approach 1:
The palm print image is divided into multiple divisional images, each of which is processed independently using the fingerprint model. This segmentation allows the system to handle the large palm print image by processing smaller manageable portions, making automated processing feasible while maintaining overall accuracy through integration of results from all divisional images.
2Extent of automation
If automated processing is applied to palm print images, then manual workload is reduced, but the complexity of the processing system increases
Solution Approach 1:
The fingerprint model, originally designed for fingerprint images, is adapted to process palm print images through the division and integration framework. This universal approach allows a single model to serve multiple purposes (fingerprint and palm print processing), reducing the need for separate specialized models while maintaining automation capability.
3Productivity
If the entire palm print image is processed at once, then processing speed is maximized, but memory requirements and processing complexity become unmanageable
Solution Approach 1:
The palm print image is segmented into multiple divisional images that are processed in parallel. This approach maintains processing speed by handling multiple regions simultaneously while reducing the complexity of individual processing tasks. The integration unit then combines the results from all divisional images to produce the final processed output.
Data Source
AI summary
An image processing apparatus includes an image division unit, an image processing unit, and an integration unit. The image division unit divides a palm print image into a plurality of divisional images. The image processing unit determines a valid region in each of the plurality of divisional images by using a fingerprint model, performs image processing that extracts core lines in each valid region, and generates respective processed divisional images corresponding to the divisional images. The integration unit generates an entire processed image corresponding to an entire of the palm print image by integrating the processed divisional images.