Handheld Printer Optical Positioning with Reduced Pixel Data
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Solution Overview
Problem
Handheld printers face challenges in maintaining print quality due to limitations in sensor capabilities, leading to lost or inaccurate printer location calculations, especially in areas without typographic structures, and require efficient processing of large pixel data for accurate positioning.
Innovation Solution
The implementation of an optical navigation system that reduces the size of position sensor signals to improve computational efficiency, using a controller to correlate previous and current location data through a correlation matrix and enhanced search algorithms, and incorporates validity checking for sensor signals to ensure accurate printing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If optical sensors sample rapidly to track printer position in random motion, then positioning accuracy is improved, but computational complexity increases due to large volumes of pixel data requiring correlation
Solution Approach 1:
The patent segments the pixel data from optical sensors into smaller manageable units for processing. Instead of correlating entire large frames, the system divides the image data into regions or features that can be processed independently, reducing the computational burden while maintaining positioning accuracy.
Solution Approach 2:
The patent extracts only the essential position information from the optical sensor data rather than processing all pixel data. By identifying and extracting key features or landmarks that indicate printer position, the system achieves accurate tracking without the computational overhead of full-frame correlation.
2Measurement precision
If correlation techniques are used to compare large amounts of pixel data between locations, then position tracking accuracy is improved, but processing time increases
Solution Approach 1:
The patent applies partial correlation by comparing only specific regions or features of the pixel data rather than performing full-frame correlation. This partial action approach maintains sufficient positioning accuracy while dramatically reducing the processing time required for real-time tracking.
Solution Approach 2:
The patent performs preliminary processing of optical sensor data to identify key features or reduce data dimensionality before correlation operations. By preparing the data in advance through feature detection or downscaling, the system enables faster correlation processing without sacrificing positioning accuracy.
3Manufacturing precision
If sensor data is processed in real-time to maintain printer location, then print quality is improved, but computational resources required increase
Solution Approach 1:
The patent replaces computationally intensive mechanical correlation algorithms with more efficient computational methods. By substituting traditional image correlation with alternative approaches such as feature matching, template matching on reduced data, or machine learning-based position estimation, the system maintains real-time processing capability with reduced computational resource consumption.
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 solution enables robust, multi-directional, and random printing with improved print quality by accurately determining printer position, reducing computational complexity, and ensuring real-time processing, even in areas without typographic structures.
Implementation Method 1
a position sensor transmits and receives light from the media
Data Source
AI summary
Methods and apparatus include a handheld printer manipulated by an operator to print an image on a media. A controller correlates a location of a printhead to the image and causes printing or not. A position sensor provides input to the controller. Its signal typifies pixels in a matrix frame indicating a current position frame and, over time, a previous position frame. The controller compares the two frames to find a presence of the previous in the current. To improve computational efficiency, the controller reduces a relative size of both frames before comparing. Specific reduction techniques contemplate converting a matrix frame of pixels indicative of previous and current locations into smaller matrices, including one-dimensional forms. Possible search areas within the current frame to look for the previous frame utilize knowledge about the movement history of the printer. Position sensor signal validity and controller architectures are other noteworthy features.