Iris Recognition Focus Assessment via Laplacian Entropy
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Solution Overview
Problem
Existing iris recognition technologies face challenges in accurately assessing the focus quality of iris images, particularly due to issues with computational complexity, robustness to image brightness and size, and interference from objects like eyeglasses frames or eyelashes, which affects the accuracy of focus assessment.
Innovation Solution
An iris recognition apparatus and method that includes an image capturing unit, a controller with an iris image cropping unit, a Laplacian image generating unit, and an entropy computing unit to assess focus quality specifically in the iris region by creating a cropped iris image, generating a Laplacian image, and calculating entropy values to determine focus scores, ensuring only properly focused images are used for recognition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the entire image or fixed partial areas are assessed for focus quality, then the assessment covers all regions, but other objects such as eyeglasses frames, eyebrows, or eyelashes interfere with the accuracy of focus assessment for the iris
Solution Approach 1:
The patent divides the image processing into distinct segments: first detecting the iris region, then cropping it out, and finally assessing focus quality only on the cropped iris image. This segmentation isolates the iris from interfering objects like eyeglasses frames, eyebrows, and eyelashes, enabling accurate focus assessment without contamination from other image regions.
Solution Approach 2:
The patent extracts the iris region from the entire image by detecting iris boundaries and cropping the image to contain only the iris portion. This extraction removes harmful interfering objects from the assessment area, allowing focus quality evaluation to be performed exclusively on the iris tissue without influence from surrounding elements.
2Measurement precision
If conventional focus assessment techniques are used, then the assessment can be performed, but the computational complexity is high
Solution Approach 1:
By extracting and cropping only the iris region before focus assessment, the patent reduces the number of pixels and computational operations required. Instead of processing the entire image or fixed large partial areas, the system processes only the relevant iris portion, significantly lowering computational complexity while maintaining assessment capability.
Solution Approach 2:
The patent applies focus assessment specifically to the local iris region rather than the entire image. This localized approach concentrates computational resources on the area of interest, reducing overall computational complexity while ensuring accurate focus evaluation where it matters most for iris recognition.
3Measurement precision
If conventional focus assessment techniques are used, then the assessment can be performed, but they are not robust to image brightness or the size of iris in the image
Solution Approach 1:
The patent segments the image to isolate the iris region through detection and cropping, creating a standardized processing target. This segmentation approach makes the subsequent focus assessment robust to variations in overall image brightness and iris size, as the assessment is performed on a consistently processed iris-only image regardless of these variations.
Solution Approach 2:
The patent changes the processing parameters by working exclusively with the cropped iris region rather than the original image parameters. This parameter change approach enables the focus assessment to be insensitive to variations in image brightness and iris size, as these variations are normalized through the cropping process that adapts to each image's specific characteristics.
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
This approach enables real-time accurate assessment of focus quality, improving the accuracy and efficiency of iris recognition by processing only high-quality iris images, thereby enhancing security and reducing computational complexity.
Implementation Method 1
The Laplacian image generating unit creates a blurred image of the cropped iris image using a Gaussian filter and then produces the Laplacian image by computing pixel-by-pixel difference between the blurred image and the cropped iris image.
Data Source
AI summary
An apparatus for recognizing an iris and an operating method thereof are provided. The iris recognition apparatus recognizing an iris of an eye includes an image capturing unit to acquire an iris image of an eye, and a controller to assess the focus quality of an iris region in the iris image and then determine an iris recognition target image.