One-Dimensional Linear Optical Sensor for Object Detection
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Solution Overview
Problem
Optoelectronic sensors, particularly photoelectric sensors, face limitations in distinguishing desired objects from other conditions, have high latency and repeatability issues, and are costly and complex to set up, making them inefficient for precise object detection and location in dynamic environments.
Innovation Solution
The use of one-dimensional linear optical sensors that capture images oriented parallel to the direction of motion, combined with advanced image processing techniques like normalized correlation pattern detection, allows for precise object detection and location with no latency, high repeatability, and reduced costs, enabling reliable detection and accurate location of objects in motion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional photoelectric sensors are used for object detection and location, then object detection capability is provided, but latency and repeatability issues occur reducing precision
Solution Approach 1:
The patent replaces traditional photoelectric sensor systems with a vision detector system that uses a two-dimensional imager and digital image analysis. This substitution of the detection mechanism eliminates the latency and repeatability issues inherent in photoelectric sensors while providing precise object location through frame-to-frame correlation analysis.
Solution Approach 2:
The patent creates a digital model (copy) of the object from one video frame and uses this model to search for and locate the object in subsequent frames. This copying approach allows for consistent, repeatable detection without the timing issues of photoelectric sensors, as the object's visual characteristics are preserved and compared across frames.
2Measurement precision
If vision detectors with two-dimensional imagers are used, then object detection accuracy is improved, but cost and system complexity increase significantly
Solution Approach 1:
The patent segments the video analysis process into distinct steps: creating an object model from one frame, searching for the model in subsequent frames, and using correlation techniques to locate the object. This segmentation of the detection process simplifies the overall system complexity while maintaining high accuracy through systematic image analysis.
Solution Approach 2:
The patent performs preliminary action by creating an object model from the first video frame before actual detection begins. This pre-processing step establishes a reference template that simplifies subsequent frame-by-frame analysis, reducing the computational complexity of real-time detection while maintaining high accuracy.
3Reliability
If photoelectric sensors are used to detect objects in specific locations, then detection capability is provided, but the ability to distinguish desired objects from other conditions is limited
Solution Approach 1:
The patent utilizes visual characteristics including color and pattern information from video frames to distinguish desired objects from other conditions. By analyzing the optical properties and visual appearance of objects in the video stream, the system can reliably identify specific objects even in complex environments where traditional photoelectric sensors would fail.
Solution Approach 2:
The patent creates a detailed visual copy of the desired object's appearance from video frames, including its color, shape, and pattern characteristics. This visual model enables the system to distinguish the desired object from other conditions by comparing the object's unique visual features against the created model, significantly improving identification reliability.
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 provides advanced object detection capabilities with high accuracy and low latency, distinguishing desired objects from other conditions, and is relatively inexpensive and easy to set up, significantly improving the reliability and precision of object location in dynamic environments.
Implementation Method 1
Photoelectric sensors, which comprise a type of optoelectronic sensor, have long been used to detect and locate objects. Such sensors typically operate by emitting a beam of light and detecting light received.
Implementation Method 2
The emitter emits a focused beam of light so that anything sufficiently reflective crossing in front of the beam reflects it back to the receiver. An object is detected when the receiver sees an amount of light above some predefined threshold.
Data Source
AI summary
Optoelectronic detection and location of moving objects is performed to capture one-dimensional images of a field of view through which objects may be moving, make measurements in those images, select from among those measurements those that are likely to correspond to objects in the field of view, make decisions responsive to various characteristics of the objects, and produce signals that indicate those decisions.