Binary Image Sensor Capture for Motion-Blur-Free Object Streams
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Solution Overview
Problem
Conventional cameras struggle with motion blur in dynamic scenes, compromising signal-to-noise ratio and image quality when capturing moving objects, especially in applications like barcode reading and quality assurance, where existing solutions either degrade resolution or fail to effectively suppress motion blur.
Innovation Solution
A high-frequency binary image sensor, such as a SPAD or QIS, captures numerous individual images at extremely short exposure times, compensating for object movement by combining them while accounting for the object's speed and geometric parameters to create a clear, high-quality composite image.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a sufficiently long exposure time is selected to accumulate sufficient charges for a favorable signal-to-noise ratio, then the signal-to-noise ratio is improved, but motion blur occurs in the image
Solution Approach 1:
The patent divides the image capture process into multiple discrete frames captured at very short exposure times (e.g., 100 ns to 10 µs). Instead of using a single long exposure that causes motion blur, the system segments the capture into many brief instances, then combines them computationally to achieve both sharpness and adequate signal accumulation.
Solution Approach 2:
The system maintains continuous capture of moving objects by recording multiple frames in rapid succession without gaps. The high frame rate ensures that the object remains in view throughout the capture sequence, allowing continuous accumulation of useful signal information while maintaining image sharpness through short individual exposures.
2Manufacturing precision
If a shorter exposure time is used to reduce motion blur, then image definition is improved, but the signal-to-noise ratio degrades
Solution Approach 1:
The patent merges multiple individual frame images, each captured with a short exposure time to maintain sharpness. By combining these frames through addition or averaging, the system accumulates sufficient signal to achieve a favorable signal-to-noise ratio while preserving the sharp image definition from the short exposures.
Solution Approach 2:
The system changes the temporal parameter of exposure time from a single long duration to multiple short durations. This parameter transformation allows the system to capture sharp images with short exposures while accumulating adequate signal through the repetition and combination of multiple such exposures.
3Reliability
If pixel grouping (binning) is applied to improve signal-to-noise ratio, then the signal-to-noise ratio is improved, but spatial resolution is lost
Solution Approach 1:
Instead of grouping pixels spatially (which loses resolution), the patent accumulates signal in the temporal dimension by capturing and combining multiple frames over time. This dimensional shift allows signal-to-noise ratio improvement without sacrificing spatial resolution, as each frame maintains full pixel detail.
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
This approach achieves a favorable signal-to-noise ratio without compromising image definition, effectively suppressing motion blur and ensuring high-quality image capture of moving objects, particularly in conveyor belt applications.
Implementation Method 1
A CMOS image sensor is typically used for the image capturing. It records images at a specific frame rate and for this purpose integrates all the charges within an exposure time that are produced by incident photons.
Data Source
AI summary
A camera device is provided that has an image sensor having a plurality of pixel elements for recording image data of an object stream of objects moving in a direction of movement relative to the camera device and a control and evaluation unit that is configured to read and further process the image data from the image sensor, wherein the image sensor is configured as a high frequency binary image sensor that generates individual images of low bit depth at a high frame rate, In this respect, the control and evaluation unit is configured to trigger a plurality of repeated shots of individual images of the image sensor and to combine the individual images while compensating the movement of the object stream between the shots to form a common image.