Laundry Sorting Using 3D Imaging for Missing or Damaged Data Carriers
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Solution Overview
Problem
Current methods for sorting laundry are either manually intensive, prone to errors, and unhygienic, or rely on data carriers that may not always be readable, leading to mixed operation and inefficiencies in automated sorting systems.
Innovation Solution
A method utilizing an imaging device to create three-dimensional images of laundry items, supplemented with additional information, allowing for automatic sorting by combining the imaging data with database-stored criteria, enabling self-learning and fully automated sorting of laundry items, even those without readable data carriers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If manual sorting is used, then sorting can be performed without automated equipment, but it requires a lot of personnel and is physically demanding and unhygienic
Solution Approach 1:
The system uses imaging devices to automatically capture images of laundry items, extract features autonomously, and perform sorting without human intervention. The database stores and compares item features, enabling the system to self-learn and improve sorting accuracy over time, eliminating the need for manual sorting personnel.
Solution Approach 2:
The patent replaces manual mechanical sorting with an automated optical system. Imaging devices capture visual information, computer vision algorithms process the data to extract features like color, shape, and fabric type, and automated mechanisms perform the physical sorting, substituting human labor with a technological system.
2Productivity
If data carriers like RFID chips are used for automated sorting, then sorting can be automated, but it is not always possible to sort laundry items with data storage media and mixed operation is required
Solution Approach 1:
The imaging device serves as an intermediary that captures visual information from laundry items. Instead of relying directly on data carriers that may fail, the system uses image-based feature extraction as a reliable intermediate step to identify and sort items, providing a backup method that works regardless of data carrier status.
Solution Approach 2:
The system changes the identification parameter from relying on electronic data carrier signals to using visual image parameters such as color, shape, texture, and pattern. This parameter transformation allows the system to identify and sort laundry items through their visual characteristics, which are always present and readable.
3Loss of information
If imaging devices are used to capture laundry items, then sorting criteria can be obtained, but additional information must be added to the recording to obtain all sorting criteria required for automatic sorting
Solution Approach 1:
The imaging device is designed to capture multiple types of information simultaneously - color, shape, size, fabric texture, and other visual features - all in a single recording. This multi-functional approach ensures that comprehensive sorting criteria are obtained without requiring multiple separate sensing devices or complex information gathering processes.
Solution Approach 2:
The system creates a digital copy of the laundry item through imaging, capturing its visual characteristics. This digital replica contains all necessary sorting information and can be stored in a database for future reference and comparison, eliminating the need to physically handle or repeatedly measure the same item.
4Measurement precision
If three-dimensional images are created of laundry items, then sorting criteria such as color, volume, fabric type and weight can be derived, but the system requires database storage and comparison capabilities
Solution Approach 1:
The system performs preliminary actions by capturing and storing three-dimensional images and extracted features in a database before the actual sorting decision is needed. This pre-processing and storage of item characteristics allows for rapid comparison and accurate sorting when items need to be categorized, separating the measurement function from the decision function.
Data Source
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AI summary
The automatic sorting of items of laundry (10) requires knowledge of all sorting criteria. Efforts are being made to read these from data carriers attached to the items of laundry (10). The problem arises when the data carriers are missing from items of laundry (10) or cannot be read, for example because they are damaged. The invention provides for deriving sorting criteria, which cannot be obtained in any other way, from at least one image recorded by an imaging device, for example a 3D camera (26). Such sorting criteria, which cannot be derived from the image or the recording of the 3D camera (26), are derived from additional information that can be obtained in various ways. It is also possible to sort items of laundry (10) fully automatically or at least largely automatically without data carriers or with damaged data carriers.