Optical Mouse Image Quality Stabilization via Brightness Contrast Analysis
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Solution Overview
Problem
Optical navigation devices, such as optical mice, experience image variations during mass production due to deviations in lenses, component assembly, light sources, and image sensors, leading to decreased image recognition accuracy.
Innovation Solution
An image quality improving method that computes brightness contrast and variation levels of original images, generates adjusted images by stabilizing brightness, and determines surface types by comparing current images with reference images, allowing for more accurate optical navigation device operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If mass production is performed, then productivity is improved, but manufacturing precision deteriorates due to deviations in lenses, component assembly, light sources, and image sensors
Solution Approach 1:
The patent applies parameter changes by adjusting brightness contrast information and brightness variation levels through computational processing. The system modifies image parameters (brightness, contrast) based on captured characteristics to compensate for manufacturing deviations, thereby maintaining image quality consistency across mass-produced devices without requiring precise manufacturing tolerances.
Solution Approach 2:
The patent implements feedback by capturing actual image characteristics from the optical navigation device, computing brightness contrast information and variation levels, and using this feedback to adjust and recalibrate the device's image processing parameters. This closed-loop approach allows the system to automatically compensate for manufacturing variations and maintain consistent performance across production batches.
2Device complexity
If image variations are present, then device complexity is reduced, but measurement precision deteriorates due to decreased image recognition accuracy
Solution Approach 1:
The patent applies self-service by enabling the optical navigation device to automatically capture its own image characteristics, compute brightness contrast information, and perform self-calibration without external intervention. The device uses its own captured images to determine calibration parameters and adjust its image processing, thereby maintaining high measurement precision while avoiding the need for complex external calibration systems.
Solution Approach 2:
The patent implements preliminary action by performing calibration computations before the optical navigation device is put into service. The system pre-computes brightness contrast information and brightness variation levels from captured images and uses these pre-calculated values to adjust subsequent image processing operations, ensuring accurate image recognition from the outset without requiring ongoing complex calibration procedures.
Data Source
AI summary
An optical navigation device control method comprising: (a) computing brightness contrast information of original images captured by an image sensor of an optical navigation device; (b) computing brightness variation levels of the original images; (c) improving image qualities of the original images based on the brightness contrast information and the brightness variation levels, to generate adjusted images; and (d) computing movements of the optical navigation device based on displacement between the adjusted images. The optical navigation device is located on a surface. The step (d) comprises: collecting reference images of different parts of the surface for a plurality of combinations of moving directions of the optical navigation device and placement directions of the surface; and determining a type of the surface via comparing images of a current surface with the reference images.