Intrinsic Image Segmentation via Single Reflectance Detection
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Solution Overview
Problem
Current computer vision applications face challenges in accurately separating illumination and material aspects of images, which affects the accuracy of object recognition and other image processing tasks.
Innovation Solution
A method and system that utilize spatio-spectral information to identify and segregate images into intrinsic images by detecting a dominant region of single reflectance, employing techniques like log chromaticity clustering, large token analysis, and spectral analysis to separate illumination and material aspects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional image processing techniques are used, then image processing can be performed, but the accuracy of separating illumination and material aspects is insufficient
Solution Approach 1:
The patent segments the image into multiple regions based on reflectance characteristics. It identifies dominant regions with single reflectance and separates the image into intrinsic images, dividing the complex task of illumination-material separation into manageable segments that can be processed independently with higher accuracy.
Solution Approach 2:
The patent applies different processing techniques to different regions of the image based on their reflectance properties. By identifying dominant regions of single reflectance and treating them differently from other regions, the system achieves locally optimized separation of illumination and material aspects, improving overall accuracy.
2Measurement precision
If complex image processing algorithms are applied to separate illumination and material aspects, then separation accuracy may improve, but computational complexity increases
Solution Approach 1:
By segmenting the image into dominant regions with single reflectance and other regions, the patent reduces computational complexity. Instead of processing the entire image uniformly with complex algorithms, the system applies simplified processing to each segment, achieving good separation accuracy with reduced computational burden.
Solution Approach 2:
The patent applies processing techniques selectively to only the necessary regions (dominant regions of single reflectance) rather than the entire image. This partial action approach maintains separation accuracy for critical regions while reducing overall computational complexity.
Data Source
AI summary
An automated, computerized method is provided for processing an image. The method includes the steps of providing an image file depicting an image, in a computer memory, identifying a dominant region of single reflectance in the image and segregating the image into intrinsic images as a function of the dominant region of single reflectance.