Fundus Image Projective Transformation Matrix Computation
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Solution Overview
Problem
Conventional methods for generating panoramic fundus images from wide-range fundus imaging fail to compute projective transformation matrices for aligning pixels of tilted images with corresponding positions in a reference image, limiting the generation of comprehensive panoramic views.
Innovation Solution
An image processing method that specifies corresponding points between reference and tilted fundus images, computes a projective transformation matrix, and applies it to transform tilted images onto the reference image, enabling the creation of a wider panoramic image by aligning pixels of tilted images with the reference image.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If conventional methods are used for generating panoramic fundus images, then the imaging process is simple, but the image coverage and alignment precision are insufficient
Solution Approach 1:
The patent replaces manual or simple mechanical image alignment methods with computational projective transformation. By using a projective transformation matrix computed from corresponding points between tilted and reference images, the system achieves precise pixel alignment without complex mechanical adjustment mechanisms, thereby improving alignment precision while maintaining operational simplicity
Solution Approach 2:
The patent transforms images using projective transformation parameters (the transformation matrix) to align pixels from tilted images with the reference image. This parameter-based transformation approach enables precise control over image geometry and positioning, achieving high alignment precision while systematically expanding the panoramic image coverage
2Area of stationary object
If projective transformation is implemented to align tilted images, then the panoramic image coverage is improved, but the computational complexity increases
Solution Approach 1:
The patent performs preliminary actions by first detecting corresponding points between tilted and reference images before computing the projective transformation matrix. This preparatory step organizes the data structure and identifies key feature points, which simplifies the subsequent matrix computation and reduces overall computational complexity while enabling comprehensive panoramic image coverage
Solution Approach 2:
The patent creates a computational model (projective transformation matrix) that copies and transforms coordinate relationships from the reference image to tilted images. This mathematical copying approach efficiently handles the transformation without requiring complex physical or mechanical systems, achieving wide panoramic coverage with manageable computational complexity
Data Source
AI summary
A first image is projective transformed into a reference image by using a projective transformation matrix on each pixel of the first image. A projective transformation matrix for transforming a tilted image n into a central image G0 is computed based on positions of combinations of twelve corresponding points indicated in a combination of the central image G0 with the tilted image n. The computed projective transformation matrix is then employed to perform a projective transformation of the tilted image n. A projective-transformed tilted image n1 is created thereby.