Image Sensor Pixel Segmentation for Low Power Change Detection
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Solution Overview
Problem
Existing change detection techniques in image processing consume excessive power and processing time due to continuous operation of all image sensor pixels, with small pixels leading to longer detection times and increased power consumption.
Innovation Solution
Implementing larger sensing pixels, strategically placed near the edges of the image sensor, which dynamically deactivate or activate based on detected changes, reducing power consumption and processing time by only activating pixels when changes are detected.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all pixels of the image sensor are continuously activated for change detection, then detection reliability is improved, but power consumption increases
Solution Approach 1:
The image sensor pixels are divided into two functional groups: a first group of pixels continuously monitors for changes, while a second group remains inactive until triggered. This segmentation allows the system to maintain detection reliability through continuous monitoring by the first group while significantly reducing overall power consumption by keeping the second group inactive until needed.
Solution Approach 2:
The system dynamically transitions pixels between active and inactive states based on detected changes. When the first group of pixels detects a change, it triggers activation of the second group. This dynamic state transition optimizes power consumption by ensuring pixels are active only when necessary for detection, while maintaining reliability through the trigger mechanism.
2Device complexity
If small pixels are used in the image sensor, then device complexity is reduced, but processing time increases
Solution Approach 1:
Different pixel sizes are used in different regions of the image sensor to optimize local detection performance. The first group of pixels may use smaller dimensions for low-power monitoring, while the second group includes larger pixels that provide faster detection capability when activated. This local differentiation of pixel quality allows the system to balance complexity and detection speed.
3Speed
If larger pixels are used for change detection, then detection speed is improved, but power consumption increases
Solution Approach 1:
The system uses periodic or event-driven activation of the second group of pixels rather than continuous operation. The first group of pixels operates continuously at low power to detect changes, and only when a change is detected does the system activate the larger, faster pixels in the second group. This periodic action pattern allows the system to achieve fast detection speed when needed while maintaining low average power consumption.
Data Source
AI summary
Methods, systems, and devices for change detection are described. The methods, systems, and devices relate to monitoring a field of view of an image sensor via a first pixel associated with a group of pixels of the image sensor, where a dimension of the first pixel exceeds a dimension of at least one pixel of the group of pixels of the image sensor, detecting a change in the field of view of the image sensor based on the monitoring, and activating a second pixel of the image sensor based on detecting the change in the field of view of the image sensor.