Hyperspectral Skin Condition Evaluation Region Segmentation
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Solution Overview
Problem
Current methods for evaluating skin condition, particularly using hyperspectral images, face high processing loads due to the need to analyze extensive image data from multiple bands, which can be computationally intensive and inefficient.
Innovation Solution
A method and apparatus that reduce processing load by allowing users to specify evaluation regions within images, generating evaluation data only for those regions, and utilizing compressed image data or hyperspectral data with partial-image reconstruction, thereby focusing processing on targeted areas and reducing data volume.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If hyperspectral image data from multiple bands is analyzed to evaluate skin condition, then measurement precision is improved, but processing load and computational complexity increase
Solution Approach 1:
The patent divides the skin evaluation task into two stages: first segmenting the image into multiple regions of interest (ROI) based on user input or automated detection, then processing each ROI separately. This segmentation allows the system to maintain high measurement precision through comprehensive multi-band analysis while reducing overall processing load by focusing computations only on relevant areas rather than the entire image.
Solution Approach 2:
The patent extracts and processes only the necessary portions of the hyperspectral image data corresponding to identified regions of interest. By taking out only the relevant data segments for analysis rather than processing the complete image dataset, the system achieves accurate skin condition evaluation in targeted areas while significantly reducing computational complexity and processing requirements.
2Measurement precision
If entire image data is processed to ensure comprehensive evaluation, then measurement precision is improved, but processing time increases
Solution Approach 1:
The patent segments the image processing task by first identifying regions of interest and then processing only those segments. This approach maintains evaluation accuracy through comprehensive analysis of relevant areas while reducing processing time by avoiding unnecessary computation on non-critical regions.
Solution Approach 2:
The patent applies partial action by processing only the necessary portions of the image data corresponding to identified skin conditions or regions of interest, rather than processing the entire image. This selective processing approach ensures adequate evaluation accuracy for actual problems while significantly reducing processing time compared to complete image analysis.
3Device complexity
If user input is required to determine evaluation region, then processing load is reduced, but ease of operation decreases
Solution Approach 1:
The patent implements self-service functionality where the system automatically identifies and determines evaluation regions without requiring manual user input. Through automated detection algorithms that analyze the hyperspectral image data, the system serves itself by autonomously selecting regions of interest, thereby maintaining low processing load while significantly improving ease of operation for end users.
Data Source
AI summary
A method for evaluating a user's skin condition, the method being performed by a computer, includes acquiring image data concerning part of the user's body and including information for four or more bands, determining an evaluation region in the part of the user's body in an image representing the part of the user's body in accordance with an input from the user, and generating, based on the image data, and outputting evaluation data representing an evaluation result of skin condition in the evaluation region.