Code Reader Motion Vector Control for Fast-Moving Barcode Decoding
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Solution Overview
Problem
Code readers face challenges in decoding machine-readable indicia due to relative motion between the object and the reader, leading to image blur and increased energy consumption when using active modes or additional hardware like Time-of-Flight sensors.
Innovation Solution
Utilizing motion vectors to track moving objects and adjust image sensor settings such as gain and exposure time, along with controlling an illumination system, to optimize decoding performance without additional hardware.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Difficulty of detecting and measuring
If code readers use active modes or additional hardware like Time-of-Flight sensors to detect motion, then motion detection capability is improved, but energy consumption increases
Solution Approach 1:
The patent replaces dedicated motion detection hardware (Time-of-Flight sensors, active monitoring systems) with an image sensor that captures visual frames. Motion is detected by comparing sequential image frames to generate motion vectors, substituting mechanical/optical detection systems with a vision-based approach that uses the image sensor's inherent capabilities.
Solution Approach 2:
The image sensor serves multiple functions: it acts as both the primary imaging device for capturing machine-readable indicia and the motion detection sensor. By processing sequential frames through image differencing algorithms, the same sensor provides both imaging and motion detection capabilities, eliminating the need for separate dedicated sensors.
2Difficulty of detecting and measuring
If code readers use stationary mode with full image analysis or presence detection sensors, then motion detection accuracy is improved, but hardware cost increases
Solution Approach 1:
The patent replaces expensive dedicated presence detection sensors with a software-based motion detection system. By using an existing image sensor and applying image differencing algorithms to sequential frames, the system achieves accurate motion detection without requiring additional hardware components.
Solution Approach 2:
The image sensor and processing system serve themselves by using the same imaging hardware to perform both imaging and motion detection functions. The system leverages its own captured image frames to detect motion, eliminating the need for external or additional sensing hardware.
3Measurement precision
If image sensor exposure time is increased to improve image quality, then imaging quality is improved, but motion blur increases for moving targets
Solution Approach 1:
The patent implements dynamic adjustment of image sensor parameters based on real-time motion detection. When motion is detected through frame comparison, the system automatically reduces exposure time to freeze motion and reduce blur. This dynamic adaptation allows the system to optimize between image quality and motion capture based on current scene conditions.
Solution Approach 2:
The system uses feedback from motion detection (comparing sequential frames) to adjust imaging parameters. Motion vectors generated from frame differencing provide feedback about scene dynamics, which then feeds back to control the image sensor's exposure time, creating a closed-loop system that adapts to motion conditions.
Data Source
AI summary
A code reader may be configured to use motion vectors to reduce blur of images when relative motion between the code reader and an object on which a code (e.g., machine-readable indicia, such as a barcode) is positioned. The motion vectors may used to calculate a frame quality factor (Q), which may enable the code reader to control components, such as an image sensor and/or illuminator. Using the quality factor, a decoder may be adjusted by replacing an image frame with a lower quality factor than one with a higher quality factor, which is more difficult to decode. The motion vectors may also enable the code reader to automatically determine that the code reader is being used to image a code so as to automatically transition from an idle phase to a decode phase.