Optical Surface Classification for Low-Power Mouse Tracking
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Solution Overview
Problem
Existing methods for surface classification in computer peripherals, such as computer mice, are resource-intensive and not suitable for battery-powered devices due to high power consumption, particularly in image processing tasks.
Innovation Solution
A computer-implemented method using an optical sensor to generate flashes and calculate a surface optical sensor flash rate, classify surface characteristics by comparing average light per pixel, and utilize a column average deviation method for accurate tracking and lift detection, employing a microcontroller and communication module.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional image processing methods are used for surface classification, then surface detection capability is improved, but power consumption increases significantly
Solution Approach 1:
The patent segments the surface classification process into distinct phases: an initial classification phase using simplified metrics (column average light values) and a subsequent tracking phase using more advanced image processing. This segmentation allows the device to use computationally expensive methods only when necessary, significantly reducing overall power consumption while maintaining detection accuracy.
Solution Approach 2:
The patent changes the processing parameters based on operational context. During surface classification, it uses simplified parameters (column averages) that consume less power, while during tracking operations, it employs more sophisticated parameters (full image processing). This dynamic parameter adjustment resolves the contradiction between detection precision and power consumption.
2Measurement precision
If complex image processing algorithms are employed for surface classification, then classification accuracy is improved, but device complexity increases
Solution Approach 1:
The patent implements a dynamic processing strategy where the complexity of image processing algorithms changes based on the operational phase. The system dynamically switches between simple column average calculations during classification and more complex full-image processing during tracking. This dynamic adaptation maintains high classification accuracy while managing device complexity through context-appropriate processing levels.
3Measurement precision
If the optical sensor operates at high flash rates for accurate tracking, then tracking precision is improved, but power consumption increases
Solution Approach 1:
The patent implements periodic action by using different flash rates for different operational phases. During surface classification, it uses a lower flash rate with simplified processing, and during active tracking, it employs higher flash rates with full image processing. This periodic variation in operational intensity maintains tracking precision when needed while reducing power consumption during transitional phases.
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
Enhances surface classification accuracy and reduces power consumption by optimizing sensor behavior across different surfaces, enabling efficient operation in battery-powered devices.
Implementation Method 1
an optical sensor generating flashes along an underlying surface... acquire an associated image having pixels and identify surface characteristics along the underlying surface
Data Source
Figure 1~2
Figure 3
AI summary
The invention deals with a computer-implemented method for operating an electronic device comprising a microcontroller and an optical sensor generating flashes along an underlying surface, the method comprising steps for: - calculating a surface optical sensor flash rate, - generating surface flashes in order to acquire an associated image having pixels and identify surface characteristics along the underlying surface, - classifying surface characteristics comprising a method of comparing a ripple of the average light detected per pixel to a threshold.