Reflection Characteristic Estimation Using Surface Orientation Segmentation
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Solution Overview
Problem
Existing image processing techniques for estimating reflection characteristics of objects are inaccurate due to the inclusion of unsuitable observed values, particularly when the object's shape results in multiple peaks in the reflection model, leading to estimation errors.
Innovation Solution
An image processing apparatus that acquires shape information and image data under various geometric conditions, determines suitable pixel positions for estimating reflection characteristics by identifying regions with similar surface orientations, and uses these positions to estimate the reflection characteristics using a unimodal reflection model.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If region-based reflection model approximation is used, then the reflection characteristic estimation can be performed efficiently, but the accuracy deteriorates due to inclusion of unsuitable observed values from multiple surface orientations
Solution Approach 1:
The patent segments the object surface into multiple reference ranges based on shape information and surface orientation. Each reference range corresponds to a specific region with consistent surface orientation, allowing the reflection model to be approximated separately for each segment. This segmentation prevents mixing observed values from different surface orientations, thereby maintaining estimation accuracy while preserving computational efficiency through localized processing.
2Device complexity
If a unimodal reflection model is used, then the model simplicity and computational ease are improved, but the ability to represent complex reflection patterns from objects with varying surface orientations deteriorates
Solution Approach 1:
The patent divides the object surface into multiple reference ranges, each with consistent surface orientation, and applies a simple unimodal reflection model to each segment separately. This segmentation strategy allows the use of computationally simple unimodal models while effectively representing complex reflection patterns across the entire object by combining results from multiple segments.
Solution Approach 2:
The patent applies the principle of local quality by using the same simple unimodal reflection model form across all reference ranges, but allowing the model parameters to vary locally for each reference range based on its specific surface orientation and shape characteristics. This enables the model to adapt to local surface properties while maintaining overall model simplicity.
Data Source
AI summary
An image processing apparatus includes first and second acquisition units, a determination unit, and an estimation unit. The first acquisition unit is configured to acquire shape information of an object. The second acquisition unit is configured to acquire a plurality of pieces of image data. The determination unit is configured to determine a pixel position corresponding to a position at which an orientation of a surface is the same as or similar to an orientation of a surface at a position of interest on the object, as a pixel position for estimating a reflection characteristic of the object at the position of interest. The estimation unit is configured to estimate the reflection characteristic of the object at the position of interest by using a pixel value at the pixel position determined by the determination unit.