Object Identification With Fixed Illumination Texture Capture
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Solution Overview
Problem
Existing image recognition technologies struggle to accurately verify objects with similar macroscopic features due to variations in ambient light and the relative position of light sources, leading to inconsistent texture feature extraction.
Innovation Solution
Utilizing a fixed illumination intensity and maintaining a consistent relative position between a light source and image sensor within an electronic device, such as a mobile phone, to stabilize ambient light and ensure accurate reflection of surface texture features.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If ambient light conditions vary, then object recognition can be performed under different lighting environments, but texture feature extraction becomes unstable and unreliable
Solution Approach 1:
The patent changes the lighting parameter from variable ambient light to controlled structured light with specific wavelengths. By using projected light patterns with fixed intensity and spectral characteristics, the system eliminates the instability caused by varying ambient light conditions while maintaining adaptability to different environments.
Solution Approach 2:
The patent introduces structured light projection as an intermediary between the light source and the object surface. This intermediary controlled light source acts as a mediator that provides consistent illumination regardless of ambient light conditions, thereby stabilizing the texture feature extraction process.
2Ease of operation
If the relative position between light source and image sensor changes, then flexible positioning is achieved, but the captured texture features become inconsistent
Solution Approach 1:
The patent implements a dynamic system where the light source and image sensor maintain a fixed relative position through coordinated movement. As the device moves, both components adjust their positions simultaneously to preserve the geometric relationship, enabling positioning flexibility while maintaining feature consistency.
Solution Approach 2:
The patent segments the lighting and sensing functions into integrated modules with fixed internal geometries. By dividing the system into modular units where the light source and sensor maintain predetermined spatial relationships, the system achieves both positioning flexibility and measurement precision.
3Speed
If macroscopic features are used for object recognition, then recognition speed is fast, but objects with similar appearances cannot be distinguished
Solution Approach 1:
The patent transitions from two-dimensional macroscopic visual features to three-dimensional microscopic surface texture features. By projecting structured light and capturing the resulting surface deformations, the system adds a depth dimension to the feature space, enabling differentiation of objects with similar appearances while maintaining fast recognition speeds.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enhances the stability of texture feature extraction, enabling reliable target verification by minimizing interference from changing light conditions and positions, thus improving the accuracy of object recognition.
Implementation Method 1
uses a light source with a fixed illumination intensity as the dominant light to shine on the target surface
Implementation Method 2
any obtained image truly reflects the scattering features of the target surface texture to light
Implementation Method 3
the light source and the image sensor always remain relatively fixed, so that any obtained image truly reflects the scattering features
Data Source
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AI summary
The present disclosure relates to a method and a server which use an electronic device to achieve target verification, wherein the electronic device includes a built-in image sensor and an auxiliary light source with a relatively fixed position relation. The method comprises turning on the light source while using the image sensor to capture an image of a target; extracting feature point information of the image; using a trained image recognition model to process the image to generate feature vectors of the image; storing the feature point information and the feature vectors for use as registration information to verify the target.