Subpixel Absolute Positioning Using Dual Speckle Databases
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Solution Overview
Problem
Existing speckle pattern positioning technologies face a trade-off between precision and speed, as methods like NCC and SIFT achieve high precision but are slow due to voluminous data, while speedy methods like SAD and SSD are limited by pixel size, making it difficult to achieve both high precision and speed in invariant speckle pattern positioning.
Innovation Solution
A subpixel absolute positioning method that captures real-time speckle patterns and uses a dual-database system with coarse-precision and fine-precision speckle coordinate patterns, employing algorithms like SAD, SSD, NCC, and SURF to quickly and precisely compare patterns, overcoming the limitations of pixel size and data volume by creating databases with optimized displacement and overlap ranges.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If pattern comparison and positioning methods such as NCC, SAD, and SSD are used, then positioning speed is improved, but positioning precision is restricted by pixel size
Solution Approach 1:
The patent divides the positioning process into two distinct stages: coarse positioning using pixel-level comparison algorithms (SAD, SSD, NCC) for speed, and fine positioning using subpixel-level algorithms for precision. This segmentation allows each stage to optimize for its specific requirement without compromise.
Solution Approach 2:
The patent performs coarse positioning first to quickly reduce the search range to a small neighborhood around the estimated position. This preliminary action prepares the system for the subsequent fine positioning stage by limiting the computational domain, thereby enabling high-precision subpixel positioning without exhaustive search.
2Measurement precision
If multi-point positioning methods such as SIFT and SURF are used, then positioning precision is improved, but calculation data volume increases and positioning speed decreases
Solution Approach 1:
The patent applies different algorithmic qualities to different regions of the search space: global pixel-level comparison for the overall pattern matching, and localized subpixel-level refinement only in the immediate neighborhood of the coarse position. This local quality differentiation reduces computational burden while maintaining precision where needed.
Solution Approach 2:
The patent performs preliminary coarse positioning to establish an initial estimate before initiating the computationally intensive subpixel refinement. This preliminary action drastically reduces the data volume required for high-precision positioning by limiting the refinement search to a small window around the coarse position, thereby improving speed without sacrificing precision.
3Measurement precision
If conventional CCD pattern comparison is used, then positioning is achieved through grayscale matching, but precision depends on contrast and sharpness which requires high-frequency space objects increasing manufacturing cost
Solution Approach 1:
The patent changes the fundamental parameter being measured from grayscale intensity (which requires high contrast and sharpness) to speckle pattern spatial distribution. By using laser speckle interference patterns and their invariant features, the system achieves high positioning precision on low-frequency surfaces where conventional grayscale methods fail, eliminating the need for expensive high-frequency manufactured objects.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This method enables rapid and precise subpixel positioning, balancing precision and speed, reducing the time required for positioning from 100 seconds to 1 second while maintaining high accuracy, as demonstrated by experiments with a speckle ruler achieving 1 μm absolute positioning precision.
Implementation Method 1
Invariant speckle patterns are interference speckle patterns generated from a sensor imaging surface as a result when a laser beam falls on an object surface and is scattered by the three-dimensional texture of the object surface
Data Source
AI summary
A quick subpixel absolute positioning device and method are introduced. The method includes the steps of (A) capturing a real-time speckle pattern of a target surface; (B) providing a coarse-precision speckle coordinate pattern and a plurality of fine-precision speckle coordinate patterns, wherein the coarse-precision speckle coordinate pattern and the fine-precision speckle coordinate patterns include a coordinate value; (C) comparing the real-time speckle coordinate pattern with the coarse-precision speckle coordinate pattern by an algorithm and then comparing the real-time speckle coordinate pattern with the fine-precision speckle coordinate patterns to obtain a coordinate value, wherein each said coarse-precision speckle coordinate pattern corresponds to a set of fine-precision speckle coordinate patterns, and the fine-precision speckle coordinate patterns are obtained when the coarse-precision speckle coordinate pattern is captured again and then captured repeatedly according to a fixed fine-precision displacement distance. Accordingly, the subpixel positioning is attained by quick comparison and manifests high precision.