Portable device with image sensor and illumination system for textile classification
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Solution Overview
Problem
Current garment care technologies require manual adjustment of ironing devices for different textiles, which is inconvenient and prone to errors due to lost care labels or improper temperature settings, leading to inefficient ironing and potential fabric damage.
Innovation Solution
A portable textile treatment device equipped with an image sensor and illumination system that classifies textiles using a convolutional neural network, allowing for automatic adjustment of operating parameters such as temperature and steam levels based on the fabric type and delicacy, eliminating the need for manual input.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the maximum temperature of the ironing device is reduced to avoid manual control, then fabric damage is prevented, but ironing time for tougher materials increases
Solution Approach 1:
The ironing device automatically detects fabric type through image capture and material recognition, then self-adjusts temperature settings without user intervention. This resolves the contradiction by eliminating the need for manual temperature control while maintaining optimal temperatures for different fabrics, preventing damage to delicate materials and ensuring efficient ironing of tougher materials.
Solution Approach 2:
The patent replaces manual mechanical temperature adjustment with an automated optical detection and recognition system. The image capture unit and material recognition unit substitute for manual user actions, automatically determining fabric type and setting appropriate temperature, thereby preventing fabric damage while maintaining productivity.
2Productivity
If manual temperature adjustment is required for optimal ironing results, then ironing efficiency is improved, but user convenience deteriorates and fabric damage risk increases
Solution Approach 1:
The device performs automatic fabric detection and temperature adjustment without requiring manual user input. The system serves itself by capturing images, recognizing materials, and autonomously setting optimal temperature parameters, thereby maintaining ironing efficiency while dramatically improving user convenience.
Solution Approach 2:
The system establishes a feedback loop where the image capture unit continuously monitors fabric type, the material recognition unit processes this information, and the control unit adjusts temperature settings accordingly. This closed-loop feedback system maintains optimal ironing efficiency while eliminating manual intervention requirements.
3Measurement precision
If care labels are used to determine temperature settings, then accurate fabric identification is achieved, but reliability deteriorates due to label loss
Solution Approach 1:
The patent replaces reliance on physical care labels with an automated image capture and material recognition system. The optical detection system directly analyzes fabric properties, eliminating the intermediary care label that can be lost or damaged, thereby maintaining accurate fabric identification while significantly improving reliability.
Solution Approach 2:
The system introduces an image capture unit and material recognition unit as intermediaries between the fabric and temperature control. Instead of relying on external care labels, the system uses optical detection and computational recognition to identify fabric type, providing a more reliable and integrated identification mechanism.
4Loss of information
If care labels are required for temperature determination, then fabric type information is provided, but device complexity increases due to manual checking
Solution Approach 1:
The device automatically captures images and recognizes fabric materials without requiring users to manually check care labels. The system self-provides fabric type information through integrated optical detection and material recognition, eliminating manual information gathering steps.
Solution Approach 2:
The system creates an optical copy of the fabric through image capture and uses this digital representation for material recognition. This copying approach replaces the need for physical care labels and manual information extraction, providing fabric type data automatically while simplifying the user interface.
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 device ensures efficient and safe ironing by accurately classifying textiles and adjusting settings accordingly, reducing ironing time for tougher materials and preventing fabric damage, while being standalone and user-friendly.
Implementation Method 1
an image sensor for taking an image of a textile
Implementation Method 2
an illumination system for illuminating a portion of the textile when said image is being taken
Data Source
Figure 1
Figure 1A
Figure 1B
AI summary
The invention relates to a portable device (1100) comprising a bottom surface (BS) intended to be in contact with a textile (TXT). The portable device comprises an image sensor (5) for taking an image of a textile, and an illumination system (6) for illuminating a portion of the textile when said image is being taken. The portable device also comprises a control unit (8a) for executing an algorithm stored in the portable device, using the taken image as an input of said algorithm, to obtain a classification of the textile. The image sensor and the control unit are integrated within the portable device. The image sensor has an active surface sensitive to light, which is oriented compared to said bottom surface (BS), with an absolute value of the orientation angle being in the range 15-70 degrees; and/or the illumination system (6) has a light source oriented compared to the said bottom surface (BS), with an absolute value of the orientation angle being in the range 15-70 degrees.