Marker Recognition Threshold Segmentation
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Solution Overview
Problem
Conventional augmented reality systems face challenges in accurately recognizing markers due to changes in pixel values caused by the surrounding environment, leading to inconsistent marker detection.
Innovation Solution
A computer-readable storage medium with an information processing program that employs image obtaining, specific object detection, first and second region information detection, and output means to improve marker recognition accuracy by calculating thresholds based on pixel values from different regions of the marker, allowing for adaptable recognition in varying environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single threshold is used for marker recognition across the entire image, then the device complexity is reduced, but the measurement precision of marker recognition deteriorates due to environmental variations
Solution Approach 1:
The patent divides the marker image into multiple regions (first region and second region) and calculates separate thresholds for each region. This segmentation allows the system to adapt to local environmental variations in different parts of the marker, improving recognition accuracy without requiring a single complex adaptive threshold for the entire image.
Solution Approach 2:
The patent applies different threshold values to different regions of the marker image based on local pixel value characteristics. By calculating region-specific thresholds from local pixel statistics, the system adapts to environmental variations in each region, maintaining high measurement precision while keeping the overall device complexity manageable.
2Measurement precision
If region-specific threshold calculation is implemented to improve marker recognition accuracy, then the measurement precision is improved, but the device complexity increases due to multiple threshold calculations
Solution Approach 1:
The patent segments the marker into a first region and a second region, calculating thresholds independently for each. This segmentation strategy improves recognition accuracy by accounting for regional environmental variations while maintaining manageable complexity through a systematic division approach rather than handling the entire image as one complex unit.
Solution Approach 2:
The patent focuses threshold calculation on specific regions of the marker that are most critical for recognition, rather than applying uniform processing across the entire image. This partial action approach improves measurement precision for key recognition areas while avoiding unnecessary computational complexity in less critical regions.
3Adaptability or versatility
If multiple regions are processed for threshold calculation, then the adaptability to environmental changes is improved, but the loss of time increases due to sequential processing of multiple regions
Solution Approach 1:
The patent divides the marker into distinct regions and processes each region independently for threshold calculation. This segmentation enables parallel processing of multiple regions, improving environmental adaptability by capturing regional variations while minimizing time loss through efficient concurrent computation rather than sequential processing.
Solution Approach 2:
The patent performs preliminary threshold calculations for each region based on local pixel value distributions before the actual marker recognition process. This preliminary action prepares region-specific thresholds in advance, allowing the system to adapt quickly to environmental changes during recognition without incurring time penalties during the critical recognition phase.
Data Source
AI summary
A computer-readable storage medium has stored therein an information processing program that causes a computer of an information processing apparatus to operate as: means for sequentially obtaining an image; means for detecting a specific object from the obtained image; means for detecting, on the basis of a first threshold and a pixel value obtained from a first region of the detected specific object, first region information on the first region; calculation means for calculating a second threshold on the basis of the pixel value obtained from the first region when the first region information is detected; means for detecting, on the basis of the second threshold calculated by the calculation means and a pixel value obtained from a second region of the detected specific object that is different from the first region, second region information on the second region; and means for outputting at least the second region information detected.