Pattern Information Registration Device Accuracy Assessment
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Solution Overview
Problem
Conventional pattern information registration methods fail to effectively determine the adequacy of pattern information data for biometric identification, as they either rely on pseudo feature points or the number of feature points without considering image quality or size, leading to difficulties in distinguishing adequate from inadequate data.
Innovation Solution
A pattern information registration device and method that calculates an identification accuracy value by forming arbitrary pattern information data with the same number of feature points as the object data, determining the degree of coincidence, and assessing adequacy based on this value, using a probability calculation to evaluate the likelihood of data being indistinguishable from other data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If conventional pattern information registration methods use the number of feature points or pseudo feature points to determine adequacy, then the determination process is simple, but the identification accuracy cannot be ensured
Solution Approach 1:
The patent introduces an identification accuracy value as an intermediary metric to bridge the gap between simple feature point counting and accurate identification assessment. This value is calculated by comparing the distribution of feature points in the input pattern information with that of arbitrary pattern information, providing a nuanced measure of adequacy that goes beyond mere quantity while remaining computationally feasible.
Solution Approach 2:
The patent transforms the determination criterion from a simple count-based parameter (number of feature points) to a distribution-based parameter (identification accuracy value). This parameter change enables more precise assessment of pattern information adequacy by considering not just how many feature points exist, but how they are distributed and whether they can be distinguished from arbitrary patterns.
2Productivity
If pattern information data with insufficient quality is registered, then registration can be executed without strict quality checks, but identification accuracy deteriorates when processing large volumes of data
Solution Approach 1:
The patent performs preliminary assessment of pattern information adequacy by calculating the identification accuracy value before registration is executed. This preliminary action filters out inadequate data early in the process, ensuring that only data meeting the accuracy threshold is registered, thereby maintaining high identification accuracy while enabling efficient processing of large data volumes.
Solution Approach 2:
The patent implements a feedback mechanism where the identification accuracy value is calculated and compared against a threshold to determine whether registration should proceed. This feedback loop ensures that registration decisions are based on objective quality metrics, preventing deterioration of identification accuracy while maintaining productive registration workflows.
3Measurement precision
If the number of feature points is increased to improve identification accuracy, then the quality of pattern information data improves, but the amount of information to be processed increases
Solution Approach 1:
The patent extracts and analyzes only the critical aspect of pattern information - the distribution characteristics of feature points - rather than processing all information equally. By focusing on the spatial distribution pattern and calculating the identification accuracy value based on this extracted feature, the system achieves high identification accuracy without being burdened by processing excessive information.
Data Source
AI summary
A pattern information registration device for selecting and registering pattern information data as an object for determination of registration for use in pattern collation includes unit which forms arbitrary pattern information data having a feature point of the same number as pattern information data of an object for determination, unit which calculates an identification accuracy value indicative of the degree of coincidence between the pattern information data as an object for determination and the arbitrary pattern information data and determines whether the pattern information data as an object for determination is adequate or not based on the identification accuracy value.