Light Source Characterization from Single Image
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional methods for estimating illumination source characteristics from images are invasive and limited in capturing lighting environment information, disrupting the image and failing to accurately determine the location and intensity of light sources.
Innovation Solution
A system and method that non-invasively determine light source characteristics by analyzing pixel data, identifying local maxima pixels around silhouette boundaries to estimate slant and tilt angles, and filtering images to separate diffuse reflectivity from shading effects, allowing for the determination of light source presence, location, and relative intensity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional methods are used to estimate illumination source characteristics, then the measurement process is invasive and disrupts the image, but the ability to capture lighting environment information is limited
Solution Approach 1:
The patent replaces invasive mechanical measurement systems with a computational vision-based system. Instead of physically measuring light sources which disrupts the image, the system uses image processing algorithms to analyze pixel data, identify local maxima pixels, and calculate light source characteristics non-invasively through software analysis.
Solution Approach 2:
The patent creates a computational model of the lighting environment by analyzing the image data. It copies the essential lighting characteristics (position, intensity, direction) into a digital representation without physically interacting with the light sources or disrupting the original image, allowing virtual reconstruction of lighting conditions.
2Measurement precision
If conventional methods are used, then the process is simple, but the location and intensity of light sources cannot be accurately determined
Solution Approach 1:
The patent segments the image analysis process into distinct functional steps: (1) identifying local maxima pixels to determine light source position, (2) analyzing pixel intensity values to determine light source intensity, and (3) calculating directional vectors to determine light source orientation. This segmentation allows each component to be optimized independently while working together to achieve accurate light source characterization.
Solution Approach 2:
The patent introduces intermediary computational elements including local maxima pixel detection algorithms, intensity thresholding mechanisms, and directional vector calculations. These intermediaries process the raw image data through multiple transformation stages to extract accurate light source characteristics that would otherwise be impossible to determine from the image alone.
Data Source
AI summary
Certain embodiments provide systems and methods for determining light source characteristics from an image. An image having pixels is received that is affected by a light source. A silhouette boundary is received. The image may be filtered to decrease diffuse reflectivity. The presence of light sources is estimated by identifying a local maxima pixel around the silhouette boundary. The local maxima pixel may be associated with the light source. A slant angle that is associated with the light source is estimated using the silhouette boundary. A tilt angle associated with the light source is estimated using the slant angle and local maxima pixel intensity. The relative intensity of each light source may be determined. The ambient light intensity of the image may be determined. The characteristics, such as the slant angle and tilt angle, may be provided to a user.