Person Feature Measurement Standardization via Hyperbolic Tangent
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Solution Overview
Problem
Existing image processing algorithms struggle to provide human-understandable rankings of digital images based on features of persons, as they generate arbitrary numerical values without clear explanations, making it difficult to interpret and connect technical measurements to meaningful representations.
Innovation Solution
A method and system that define features of persons, measure data points using a first algorithm, generate distribution curves, and standardize values using a hyperbolic tangent function transformation to achieve meaningful and interpretable results within a closed range of 0 to 1, enabling easy human interpretation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional algorithms are used to measure image features, then measurement precision is achieved, but the output values are arbitrary and not human understandable
Solution Approach 1:
The patent transforms the output parameters of feature measurement algorithms from arbitrary numerical values to standardized values within a closed range (0 to 1). This is achieved by introducing a transformation function that maps raw measurement values to a standardized scale, making the results human-understandable while preserving the original measurement precision. The transformation maintains the relative ordering of features while presenting them in an interpretable format.
2Measurement precision
If raw numerical values are used directly, then measurement accuracy is maintained, but ease of operation for human interpretation deteriorates
Solution Approach 1:
The patent introduces a transformation function as an intermediary between the raw feature measurement algorithm and the human user. This intermediary component takes the accurate but arbitrary numerical values from the measurement algorithm and converts them into standardized values within a closed range (0 to 1), which are easier for humans to interpret and compare. The intermediary preserves the underlying accuracy while improving usability.
3Adaptability or versatility
If arbitrary measurement scales are used, then algorithmic flexibility is maintained, but adaptability to human understanding deteriorates
Solution Approach 1:
The patent changes the parameter scale of feature measurements from arbitrary algorithms-specific scales to a universal standardized scale (0 to 1). This transformation enables adaptability across different feature types and algorithms while maintaining a consistent, human-understandable output format. The standardized scale allows for easy comparison and interpretation regardless of the underlying measurement algorithm used.
Data Source
AI summary
A method and a system for measuring a feature of persons. The method includes defining the feature of persons being measured. The method further includes measuring values of data points from a sample of digital images comprising the persons, according to the defined feature by a first algorithm. The method further includes generating a distribution curve of the measured values. The method further includes standardizing the measured values by implementing a hyperbolic tangent function transformation.