Object Authentication Variation Image Generation
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Solution Overview
Problem
Conventional object authentication techniques struggle to accurately generate variation images reflecting real-world illumination conditions, especially in environments with complex lighting, leading to limited collation accuracy.
Innovation Solution
An information processing apparatus that captures images of objects in real environments, measures illumination conditions, and generates variation images based on three-dimensional data and measured illumination conditions, enabling accurate collation by comparing feature amounts between captured and registered images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If a two-dimensional image or standard three-dimensional model is used to generate variation images, then the generation process is simple, but the accuracy of reflecting real illumination conditions and irregularities on the object is insufficient
Solution Approach 1:
The patent transitions from two-dimensional images to three-dimensional models with irregularities to generate variation images. By using 3D models that incorporate surface irregularities and applying illumination distribution data captured from real environments, the system achieves accurate reflection of real illumination conditions while maintaining computational feasibility.
2Device complexity
If a simple illumination model with position and angle parameters is used, then the model is easy to implement, but it cannot accurately represent complicated illumination conditions in real environments
Solution Approach 1:
The patent moves from simple illumination parameters (position and angle) to a comprehensive illumination distribution representation. By capturing illumination distribution as detailed data from the real environment and applying it to 3D models, the system accurately represents complicated illumination conditions including multiple light sources, shadows, and environmental reflections.
3Productivity
If conventional variation image generation methods are used, then the processing is computationally efficient, but the collation accuracy is limited due to inability to accurately reflect real illumination conditions
Solution Approach 1:
The patent performs preliminary capture and storage of illumination distribution data from real environments. This pre-captured illumination data is then applied to 3D models during variation image generation, enabling accurate collation under matching illumination conditions while maintaining efficient processing through pre-computed illumination characteristics.
Data Source
AI summary
Information processing apparatus includes an input unit configured to input a captured image capturing a target object in a real environment, an obtaining unit configured to obtain an illumination condition in the real environment; a generation unit configured to generate a variation image as an image of a registration object reflecting the illumination condition based on three-dimensional data of the registration object and the obtained illumination condition, and a collation unit configured to collate the registration object with the target object based on a feature amount of the variation image and a feature amount of the captured image.