Optical Sensor ROI Detection Using Distance and Remission Data
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Solution Overview
Problem
Existing object sensing systems using camera systems face high computational demands for real-time image evaluation, and current pre-processing algorithms for identifying regions of interest (ROIs) are unreliable due to their reliance on pixel gray value thresholds, which can fail to distinguish objects from backgrounds.
Innovation Solution
Integration of a distance measurement device or remission measurement device with the optical sensor to determine object spacings and remission behavior, allowing for accurate identification of ROIs independent of image data, thereby reducing computational load and improving reliability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If pre-processing algorithms use simple gray value thresholding to identify ROIs, then the computational load is reduced, but the reliability of ROI detection deteriorates because objects cannot be reliably distinguished from backgrounds
Solution Approach 1:
The patent introduces an intermediary pre-processing stage that operates on the complete sensed image data before ROI identification. This pre-processing generates enhanced image data or intermediate representations that preserve object-background distinctions without requiring full image evaluation, thereby enabling reliable ROI detection while maintaining reduced computational load during subsequent processing stages.
Solution Approach 2:
The patent applies preliminary action by performing pre-processing operations on the complete image data before the main ROI identification and evaluation stages. This preliminary processing prepares the data in advance to facilitate more reliable object detection in subsequent steps, allowing the system to achieve high detection reliability without proportionally increasing the computational burden during real-time operation.
2Reliability
If the complete sensed image data is processed for ROI identification, then detection reliability improves, but the computational power required increases significantly
Solution Approach 1:
The patent segments the image processing task into distinct stages: a pre-processing stage that operates on complete image data to generate enhanced representations, followed by ROI identification and evaluation stages that process only the relevant regions. This segmentation allows reliable detection based on complete data while avoiding the computational expense of processing all image data at full resolution throughout the entire evaluation pipeline.
Solution Approach 2:
The patent applies partial action by performing comprehensive pre-processing on the complete image data, then limiting subsequent processing to only the identified ROIs. This approach uses excessive action (complete data processing) only where necessary for reliable detection, while using partial action (ROI-limited processing) for the majority of the evaluation workload, thereby balancing reliability with computational efficiency.
3Device complexity
If simple threshold algorithms are used for ROI determination, then the device complexity is reduced, but the adaptability to different object-background scenarios deteriorates
Solution Approach 1:
The patent introduces a pre-processing intermediary that enhances the capabilities of simple threshold algorithms without increasing their inherent complexity. This pre-processing stage prepares the image data to make objects and backgrounds more distinguishable, allowing simple algorithms to adapt to various scenarios while maintaining low device complexity. The pre-processing acts as a mediator that bridges the gap between simple algorithms and complex detection requirements.
Data Source
AI summary
The invention relates to an apparatus and a method for the sensing of objects moved through the field of view of an optical sensor comprising a device for the selection of regions of interest which are each associated only with a part of the field of view of the optical sensor, wherein a distance measurement device and/or a remission measurement device is/are integrated into the optical sensor or is/are connected in front of it or after it in the direction of movement of the objects, with the distance measurement device and/or the remission measurement device being designed for the determination of the spacing and/or of the remission of the object surfaces facing the distance measurement device and/or the remission measurement device and being coupled to an evaluation circuit for the calculating of the regions of interest in dependence on the determined spacings and/or remissions.