3D Multilayer Skin Texture Recognition via Hyperspectral Imaging

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Solution Overview

Problem

Conventional face recognition techniques are unreliable and inaccurate due to illumination and pose variations, making it difficult to detect faces in uncontrolled environments with varying lighting and orientations.

Innovation Solution

A three-dimensional multilayer skin texture recognition system using hyperspectral imaging to extract microstructure skin signatures, characterized by weighted subtraction of reflectance at different wavelengths, allowing for robust face recognition irrespective of illuminations, facial poses, and expressions.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of manufacture

If conventional two-dimensional face recognition techniques are used, then the system is simple to implement, but the recognition accuracy deteriorates under varying illumination and pose conditions

Engineering Contradiction:

Improveimplementation simplicityVSAvoidrecognition accuracy under illumination and pose variations

Core Design Contradiction:

Ease of manufactureVSReliability

Solution Approach 1:

The patent transitions from two-dimensional image-based recognition to three-dimensional volumetric skin texture recognition. By capturing and processing 3D facial data including depth information and multiple tissue layers, the system achieves robustness against illumination and pose variations while maintaining practical implementability through structured light scanning and multi-layer optical processing

Inventive Principle:

Principle #17Another dimension (Dimensionality change)

2Adaptability or versatility

If three-dimensional facial models are reconstructed from uncontrolled environment images, then the system can operate in uncontrolled environments, but the measurement precision deteriorates due to illumination and pose variations

Engineering Contradiction:

Improveoperation in uncontrolled environmentsVSAvoidfacial feature measurement accuracy

Core Design Contradiction:

Adaptability or versatilityVSMeasurement precision

Solution Approach 1:

The patent segments the facial tissue into multiple volumetric layers (epidermis, dermis, subcutaneous tissue) and processes each layer separately using wavelength-specific optical signals. This segmentation allows precise measurement of skin texture features in each layer while being insensitive to external illumination variations, thereby maintaining measurement precision in uncontrolled environments

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system uses multiple wavelengths of optical radiation to probe different depths of skin layers. By changing the wavelength parameter, the system can selectively penetrate and characterize specific tissue depths, enabling precise measurement of volumetric skin texture features independent of surface illumination conditions and facial pose

Inventive Principle:

Principle #35Parameter changes

3Device complexity

If pixel values are used for image comparison, then the comparison process is simple, but the reliability deteriorates due to illumination variation effects

Engineering Contradiction:

Improvecomparison process complexityVSAvoidimage comparison reliability

Core Design Contradiction:

Device complexityVSReliability

Solution Approach 1:

The patent replaces traditional mechanical/optical image comparison based on pixel intensity values with a computational approach that analyzes volumetric skin texture features across multiple tissue layers. This substitution uses digital signal processing of optical reflectance patterns from different skin depths, providing illumination-invariant comparison that maintains reliability while managing complexity through algorithmic processing

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

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

The system provides efficient and accurate non-cooperative face recognition, capable of identifying individuals with higher accuracy and robustness to environmental variations, suitable for applications like homeland security and biometrics.

Implementation Method 1

The micro structure skin signature may be characterized utilizing a weighted subtraction of reflectance at different wavelengths that captures different layers under the skin surface

Methodology Applied

Scientific EffectReflectance: Reflection

Data Source

PatentUS8634596B2Three-dimensional multilayer skin texture recognition system and method

Publication Date: 2014.01.21 HONEYWELL INTERNATIONAL INC

AI summary

A three-dimensional multilayer skin texture recognition system and method based on hyperspectral imaging. Three-dimensional facial model associated with an object may be acquired from a three-dimensional image capturing device. A face reconstruction approach may be implemented to reconstruct and rewarp the three-dimensional facial model to a frontal face image. A hyperspectral imager may be employed to extract a micro structure skin signature associated with the skin surface. The micro structure skin signature may be characterized utilizing a weighted subtraction of reflectance at different wavelengths that captures different layers under the skin surface via a multilayer skin texture recognition module. The volumetric skin data associated with the face skin can be classified via a volumetric pattern.