Motion Encoder Using Near-Sensor Image Processing for Energy Efficiency
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Solution Overview
Problem
Conventional optical motion encoders are costly and energy demanding, making them impractical for certain applications, especially with the increasing demand for cost and energy-efficient sensors in the Internet of Things (IoT) era.
Innovation Solution
A motion encoder that uses Near-Sensor Image Processing (NSIP) architecture to compute the duration of local extreme points in image frames, allowing for efficient motion estimation without the need for complex hardware, thereby reducing processing requirements and energy consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional optical motion encoders are used, then motion measurement accuracy is improved, but cost and energy consumption increase
Solution Approach 1:
The patent segments the motion measurement task into discrete image frame acquisitions and local extreme point detections at specific pixel positions, rather than continuous processing. This allows the system to achieve accurate motion measurement through periodic sampling while reducing overall energy consumption compared to conventional continuous processing methods.
Solution Approach 2:
The patent extracts only the essential information needed for motion measurement by identifying local extreme points at specific pixel positions in image frames. This extraction approach eliminates the need for complex full-image processing, thereby reducing energy consumption while maintaining measurement accuracy.
2Measurement precision
If conventional optical motion encoders are used, then motion measurement accuracy is improved, but device complexity increases
Solution Approach 1:
The patent extracts only the essential information needed for motion measurement by identifying local extreme points at specific pixel positions in image frames. This extraction approach eliminates the need for complex full-image processing, thereby reducing device complexity while maintaining measurement accuracy.
Solution Approach 2:
The patent uses image frames as copies of the visual scene at different time points, allowing motion analysis without directly manipulating the physical object or requiring complex mechanical encoders. This copying approach simplifies the device architecture while preserving measurement capabilities.
3Measurement precision
If Doppler laser is used, then motion measurement accuracy is improved, but cost increases
Solution Approach 1:
The patent uses standard image sensing circuitry to create digital copies of the visual scene, replacing the need for expensive Doppler laser equipment. This copying approach achieves motion measurement functionality through affordable digital imaging technology while maintaining measurement accuracy.
Solution Approach 2:
The patent employs standard, inexpensive image sensors and processing methods rather than expensive specialized equipment like Doppler lasers. The system uses readily available image sensing circuitry that can be manufactured at low cost, making the technology economically viable for widespread deployment.
4Measurement precision
If conventional camera and image processing are used, then motion measurement capability is achieved, but energy consumption and processing requirements increase
Solution Approach 1:
The patent segments the image processing task by focusing computation only on specific pixel positions where local extreme points are detected, rather than processing the entire image. This segmentation dramatically improves processing efficiency by reducing the computational domain to only the relevant portions of the image data.
Solution Approach 2:
The patent extracts only the essential motion information by identifying local extreme points at specific pixel positions, eliminating the need for complex full-image processing. This extraction methodology achieves motion measurement capability while significantly reducing processing requirements and energy 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
Enables the development of cost-effective and energy-efficient optical/non-contact motion encoders that are suitable for various applications, including those in the IoT, by simplifying the processing of motion data and integrating image sensing and processing within a single unit.
Implementation Method 1
optical techniques based on sensing of light can be used instead
Data Source
AI summary
Method and motion encoder for providing a measure indicative of motion of an object. The indicated motion is relative to an image sensing circuitry and in a direction that is perpendicular to an optical axis of the image sensing circuitry when the image sensing circuitry provides image frames sequentially imaging at least part of said object during the motion. The motion encoder obtains image data of a sequence of said image frames and then computes, for at least one pixel position of said sequence of image frames and based on the obtained image data, at least one duration value. Each duration value indicating a duration of consecutively occurring local extreme points in said sequence of image frames. The motion encoder then provides, based on said at least one duration value, said measure indicative of the motion.