Object Recognition Illumination for Waste Segregation
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Solution Overview
Problem
Existing recyclable waste auto-segregation devices face challenges in accurately extracting and calculating the position of recyclable waste due to issues like overexposure from glossy surfaces and light transmissive materials, which can lead to incorrect segregation.
Innovation Solution
An object recognition device that illuminates objects under multiple conditions, capturing images with different light intensities and ultraviolet light to enhance image processing and accurately determine object position, allowing for precise segregation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single illumination condition is used for imaging, then the device complexity is reduced, but the measurement precision of object position deteriorates due to overexposure and light transmissivity issues
Solution Approach 1:
The illumination system dynamically switches between multiple illumination conditions (first and second illumination conditions) based on object characteristics. The controller adjusts illumination parameters in real-time to capture images under optimal conditions for different material types, resolving the contradiction between device simplicity and measurement precision.
Solution Approach 2:
The system changes illumination parameters (intensity, wavelength, direction) to capture images under different conditions. By taking images at first and second illumination conditions and synthesizing them, the system achieves precise position measurement for both light-transmissive and glossy objects without requiring complex hardware modifications.
2Measurement precision
If multiple illumination conditions are used to improve image quality, then the measurement precision improves, but the productivity decreases due to multiple imaging cycles
Solution Approach 1:
The system uses periodic illumination switching between first and second conditions, capturing images in rapid succession. The controller coordinates the imaging cycles to minimize total processing time while ensuring both image types are captured, maintaining productivity while achieving precise position measurement through image synthesis.
Solution Approach 2:
The system merges multiple images taken under different illumination conditions into a single synthesized image for position calculation. This combining approach allows the system to leverage information from both illumination conditions simultaneously, achieving high measurement precision without requiring sequential processing of multiple images, thus maintaining productivity.
3Ease of operation
If standard illumination is used for all objects, then the ease of operation is maintained, but the reliability of object recognition deteriorates for light transmissive and glossy materials
Solution Approach 1:
The system automatically detects object characteristics (light transmissivity, glossiness) and self-adjusts the illumination conditions without user intervention. The controller selects appropriate illumination conditions and synthesizes images automatically, maintaining ease of operation while significantly improving recognition reliability for challenging materials.
Solution Approach 2:
The system uses feedback from image analysis to determine whether additional illumination conditions are needed. Based on the quality of initial images and object characteristics, the controller decides whether to capture images under second illumination conditions, optimizing both operational simplicity and recognition reliability through adaptive feedback control.
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
The solution effectively reduces overexposure and improves image extraction, enabling accurate calculation of object position and segregation, even for materials like glass and polyethylene terephthalate, by using high-light, low-light, and fluorescence images.
Implementation Method 1
an illuminator that illuminates the object
Implementation Method 2
take a second-type image of the object when the object is illuminated by the illuminator under a second illumination condition different than the first illumination condition
Implementation Method 3
an imager that takes a first-type image of the object when the object is illuminated by the illuminator under a first illumination condition, and takes a second-type image of the object when the object is illuminated by the illuminator under a second illumination condition different than the first illumination condition
Data Source
AI summary
An object recognition device includes an illuminator configured to illuminate an object, an imager configured to take a first-type image of the object when the object is illuminated by the illuminator under a first illumination condition, and take a second-type image of the object when the object is illuminated by the illuminator under a second illumination condition different than the first illumination condition, and circuitry configured to calculate a position of the object based on the first-type image and the second-type image.