Optical Mouse Wake-Up via Histogram Difference Analysis
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Solution Overview
Problem
Existing wake-up algorithms for wireless optical mice, such as pixmon, de-correlation, and SQUAL, are either inaccurate or consume excessive power due to complex computations, making them inefficient for determining movement and waking up from sleep mode.
Innovation Solution
A wake-up method that analyzes the histogram of pixel variations between frames captured during sleep mode, using a reference frame and compare frames to determine if the optical input device has been moved, without requiring complex image processing techniques, thereby reducing power consumption and improving accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If complex image processing techniques such as de-correlation algorithm or SQUAL wakeup algorithm are used to detect movement, then measurement precision of movement detection is improved, but use of energy increases due to complex computations like DCR filtering and image correlation
Solution Approach 1:
The patent segments the image processing task by dividing the frame into multiple regions (e.g., quadrants) and computing histogram differences for each region separately. This allows the system to focus computational effort on specific areas of interest while reducing the overall computational burden compared to processing the entire frame with complex algorithms like de-correlation or SQUAL.
Solution Approach 2:
The patent replaces complex mechanical/image processing computations (such as DCR filtering and full-frame image correlation) with a simpler statistical approach using histogram analysis. By substituting intensive computational mechanics with lighter statistical operations, the system achieves acceptable movement detection accuracy with significantly reduced power consumption.
2Use of energy by moving object
If simple wakeup algorithm such as pixmon is used to check pixel value variation, then use of energy is reduced, but measurement precision of movement detection deteriorates as it cannot accurately detect whether the device has been moved
Solution Approach 1:
The patent transitions from analyzing individual pixel values (one-dimensional approach) to analyzing histogram distributions (adding a statistical dimension). By computing histogram differences and comparing peak values, the system gains more robust movement detection capability while maintaining low computational complexity and power consumption.
Solution Approach 2:
The patent changes the detection parameter from raw pixel value variations to histogram peak value differences. This parameter transformation enables the system to detect movement more accurately by focusing on the distribution characteristics of pixel values rather than individual pixel changes, thereby improving measurement precision without significantly increasing energy consumption.
3Measurement precision
If histogram analysis of pixel variations is performed to determine movement, then measurement precision of movement detection is improved, but device complexity increases due to additional processing steps
Solution Approach 1:
The patent extracts only the essential information needed for movement detection by computing histogram differences and focusing on peak value comparisons. By taking out and analyzing only the most relevant statistical features rather than processing the entire image data, the system achieves accurate movement detection with minimal processing complexity.
Data Source
AI summary
An exemplary embodiment of the present disclosure provides a wake up method and an optical input device using the same. The method includes the following steps. A first image is captured and set as a reference frame when the optical input device enters a sleep mode. A second image is captured and set as a compare frame while the optical input device operates in the sleep mode. The second frame is further being compared with the reference frame to generate a histogram difference. Subsequently, whether a peak histogram value of the histogram difference is less than a predetermined threshold is determined. When the determined that the peak histogram value is less than the predetermine threshold, configures the optical input device to operate in an active mode.