Quasi-Periodic Pattern for Image Position Detection
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Solution Overview
Problem
Current image capture technologies lack effective methods to determine if a target area within an image is properly positioned, oriented, and within acceptable resolution, leading to potential cropping and suboptimal image quality.
Innovation Solution
The use of a quasi-periodic pattern border surrounding the target area, which is detected by a processor to determine if the target area is within the image frame, providing feedback to the user on alignment and resolution, allowing for aesthetically pleasing and efficient image capture.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If traditional image capture methods are used without position detection patterns, then the image capture process is simple, but the target area may be cropped or improperly positioned leading to suboptimal image quality
Solution Approach 1:
A quasi-periodic pattern border is introduced as an intermediary element between the target area and the image capture system. This pattern serves as a mediator that enables precise position and orientation detection without requiring complex hardware modifications. The pattern border acts as a reference that the processor can analyze to determine capture quality metrics.
Solution Approach 2:
The quasi-periodic pattern border is placed around the target area in advance before image capture. This preliminary positioning of reference markers allows the system to pre-assess whether the target will be properly captured, enabling real-time feedback to the user about alignment and resolution adequacy before the actual capture occurs.
2Measurement precision
If a quasi-periodic pattern border is added to enable precise position detection, then target area positioning accuracy improves, but the complexity of the image capture system increases
Solution Approach 1:
The patent replaces complex mechanical or hardware-based position detection systems with a software-based image processing approach. Instead of using specialized sensors or mechanical alignment devices, the system uses standard image capture hardware combined with algorithmic analysis of the quasi-periodic pattern, substituting mechanical complexity with computational processing.
Solution Approach 2:
The system changes the visual parameters of the border by using a quasi-periodic pattern with specific frequency characteristics. This pattern design allows the processor to detect position and orientation information through frequency analysis, transforming spatial positioning problems into frequency domain measurements that can be processed efficiently.
3Reliability
If real-time position and orientation detection is implemented, then image capture quality is improved, but the processing time and computational resources increase
Solution Approach 1:
The processor analyzes only the quasi-periodic pattern border region rather than the entire image to determine position and orientation. By focusing computational resources on the specific pattern border areas that contain the reference information, the system achieves reliable quality assessment with reduced processing time compared to analyzing the full image content.
Data Source
AI summary
Examples disclosed herein relate to determining image capture position information based on a quasi-periodic pattern. For example, a processor may determine whether a target area is within a captured image based on the detection of a quasi-periodic pattern in a first detection area and in a second detection area of the captured image.